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Books and Theses
- 2014
[b1]Tomasz Trzcinski:
Learning and Matching Binary Local Feature Descriptors. EPFL, Switzerland, 2014
Journal Articles
- 2024
- [j26]Valeriya Khan
, Sebastian Cygert, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski:
Looking Through the Past: Better Knowledge Retention for Generative Replay in Continual Learning. IEEE Access 12: 45309-45317 (2024) - [j25]Monika Wysoczanska, Tom Monnier, Tomasz Trzcinski, David Picard:
Toward Unsupervised Visual Reasoning: Do Off-the-Shelf Features Know How to Reason? IEEE Access 12: 76367-76378 (2024) - [j24]Lukasz Struski, Pawel M. Morkisz, Przemyslaw Spurek, Samuel Rodriguez Bernabeu, Tomasz Trzcinski:
Efficient GPU implementation of randomized SVD and its applications. Expert Syst. Appl. 248: 123462 (2024) - [j23]Dominik Zimny, Joanna Waczynska, Tomasz Trzcinski, Przemyslaw Spurek:
Points2NeRF: Generating Neural Radiance Fields from 3D point cloud. Pattern Recognit. Lett. 185: 8-14 (2024) - 2023
- [j22]Witold Oleszkiewicz, Dominika Basaj, Igor Sieradzki, Michal Górszczak, Barbara Rychalska, Koryna Lewandowska, Tomasz Trzcinski, Bartosz Zielinski:
Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations. IEEE Access 11: 13028-13043 (2023) - [j21]Szymon Plotka, Michal K. Grzeszczyk, Robert Brawura-Biskupski-Samaha, Pawel Gutaj, Michal Lipa, Tomasz Trzcinski, Ivana Isgum, Clara I. Sánchez, Arkadiusz Sitek:
BabyNet＋＋: Fetal birth weight prediction using biometry multimodal data acquired less than 24 hours before delivery. Comput. Biol. Medicine 167: 107602 (2023) - [j20]Maciej Zamorski, Michal Stypulkowski, Konrad Karanowski, Tomasz Trzcinski, Maciej Zieba:
Continual learning on 3D point clouds with random compressed rehearsal. Comput. Vis. Image Underst. 228: 103621 (2023) - [j19]Bartosz Wójcik, Marcin Przewiezlikowski, Filip Szatkowski, Maciej Wolczyk, Klaudia Balazy, Bartlomiej Krzepkowski, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski:
Zero time waste in pre-trained early exit neural networks. Neural Networks 168: 580-601 (2023) - [j18]Ivan Kostiuk, Przemyslaw Stachura, Slawomir Konrad Tadeja, Tomasz Trzcinski, Przemyslaw Spurek:
HyperColor: A HyperNetwork Approach for Synthesizing Autocolored 3-D Models for Game Scenes Population. IEEE Trans. Games 15(4): 613-622 (2023) - 2022
- [j17]Wojciech Masarczyk, Pawel Wawrzynski, Daniel Marczak, Kamil Deja, Tomasz Trzcinski:
Logarithmic Continual Learning. IEEE Access 10: 117001-117010 (2022) - [j16]Przemyslaw Spurek, Maciej Zieba, Jacek Tabor, Tomasz Trzcinski:
General Hypernetwork Framework for Creating 3D Point Clouds. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9995-10008 (2022) - [j15]Jacek Komorowski, Monika Wysoczanska, Tomasz Trzcinski:
EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale. IEEE Robotics Autom. Lett. 7(2): 722-729 (2022) - 2021
- [j14]Kamil Deja, Jan Dubinski, Piotr Nowak, Sandro Wenzel, Przemyslaw Spurek, Tomasz Trzcinski:
End-to-End Sinkhorn Autoencoder With Noise Generator. IEEE Access 9: 7211-7219 (2021) - [j13]Michal Stypulkowski, Kacper Kania, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski, Jan Chorowski:
Representing point clouds with generative conditional invertible flow networks. Pattern Recognit. Lett. 150: 26-32 (2021) - 2020
- [j12]Maciej Zamorski, Maciej Zieba, Piotr Klukowski, Rafal Nowak, Karol Kurach, Wojciech Stokowiec, Tomasz Trzcinski:
Adversarial autoencoders for compact representations of 3D point clouds. Comput. Vis. Image Underst. 193: 102921 (2020) - 2019
- [j11]Ivona Tautkute, Tomasz Trzcinski, Aleksander Skorupa, Lukasz Brocki, Krzysztof Marasek:
DeepStyle: Multimodal Search Engine for Fashion and Interior Design. IEEE Access 7: 84613-84628 (2019) - [j10]Michal Komorowski, Tomasz Trzcinski:
Random Binary Search Trees for approximate nearest neighbour search in binary spaces. Appl. Soft Comput. 79: 87-93 (2019) - [j9]Ivona Tautkute, Tomasz Trzcinski:
Classifying and Visualizing Emotions with Emotional DAN. Fundam. Informaticae 168(2-4): 269-285 (2019) - [j8]Maciej Pesko, Adam Svystun, Pawel Andruszkiewicz, Przemyslaw Rokita, Tomasz Trzcinski:
Comixify: Transform Video Into Comics. Fundam. Informaticae 168(2-4): 311-333 (2019) - [j7]Michal Sypetkowski, Grzegorz Sarwas, Tomasz Trzcinski:
Synthetic Image Translation for Football Players Pose Estimation. J. Univers. Comput. Sci. 25(6): 683-700 (2019) - 2018
- [j6]Adam Bielski, Tomasz Trzcinski:
Understanding Multimodal Popularity Prediction of Social Media Videos With Self-Attention. IEEE Access 6: 74277-74287 (2018) - 2017
- [j5]Tomasz Trzcinski, Przemyslaw Rokita:
Predicting Popularity of Online Videos Using Support Vector Regression. IEEE Trans. Multim. 19(11): 2561-2570 (2017) - 2015
- [j4]Tomasz Trzcinski, C. Mario Christoudias, Vincent Lepetit:
Learning Image Descriptors with Boosting. IEEE Trans. Pattern Anal. Mach. Intell. 37(3): 597-610 (2015) - 2014
- [j3]Bin Fan, Qingqun Kong, Tomasz Trzcinski, Zhiheng Wang, Chunhong Pan, Pascal Fua:
Receptive Fields Selection for Binary Feature Description. IEEE Trans. Image Process. 23(6): 2583-2595 (2014) - 2012
- [j2]Michael Calonder, Vincent Lepetit, Mustafa Özuysal, Tomasz Trzcinski, Christoph Strecha, Pascal Fua:
BRIEF: Computing a Local Binary Descriptor Very Fast. IEEE Trans. Pattern Anal. Mach. Intell. 34(7): 1281-1298 (2012) - [j1]Tomasz Trzcinski, Vincent Lepetit, Pascal Fua:
Thick boundaries in binary space and their influence on nearest-neighbor search. Pattern Recognit. Lett. 33(16): 2173-2180 (2012)
Conference and Workshop Papers
- 2024
- [c77]Magdalena Proszewska, Marcin Mazur, Tomasz Trzcinski, Przemyslaw Spurek:
HyperCube: Implicit Field Representations of Voxelized 3D Models (Student Abstract). AAAI 2024: 23623-23625 - [c76]Tomasz Trzcinski, Bartlomiej Twardowski, Bartosz Zielinski, Kamil Adamczewski, Bartosz Wójcik:
Zero-Waste Machine Learning. ECAI 2024: 43-49 - [c75]Daniel Marczak, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski:
Revisiting Supervision for Continual Representation Learning. ECCV (6) 2024: 181-197 - [c74]Michal Bortkiewicz, Jakub Lyskawa, Pawel Wawrzynski, Mateusz Ostaszewski, Artur Grudkowski, Bartlomiej Sobieski, Tomasz Trzcinski:
Subgoal Reachability in Goal Conditioned Hierarchical Reinforcement Learning. ICAART (1) 2024: 221-230 - [c73]Przemyslaw Spurek, Sebastian Winczowski, Maciej Zieba, Tomasz Trzcinski, Kacper Kania, Marcin Mazur:
Modeling 3D Surfaces with a Locally Conditioned Atlas. ICCS (2) 2024: 100-115 - [c72]Grzegorz Rypesc, Sebastian Cygert, Valeriya Khan, Tomasz Trzcinski, Bartosz Zielinski, Bartlomiej Twardowski:
Divide and not forget: Ensemble of selectively trained experts in Continual Learning. ICLR 2024 - [c71]Michal Nauman, Michal Bortkiewicz, Piotr Milos, Tomasz Trzcinski, Mateusz Ostaszewski, Marek Cygan:
Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning. ICML 2024 - [c70]Tomasz Szczepanski, Michal K. Grzeszczyk, Szymon Plotka, Arleta Adamowicz, Piotr Fudalej, Przemyslaw Korzeniowski, Tomasz Trzcinski, Arkadiusz Sitek:
Let Me DeCode You: Decoder Conditioning with Tabular Data. MICCAI (3) 2024: 228-238 - [c69]Michal K. Grzeszczyk, Przemyslaw Korzeniowski, Samer Alabed, Andrew J. Swift, Tomasz Trzcinski, Arkadiusz Sitek:
TabMixer: Noninvasive Estimation of the Mean Pulmonary Artery Pressure via Imaging and Tabular Data Mixing. MICCAI (5) 2024: 670-680 - [c68]Michal K. Grzeszczyk, Tomasz Trzcinski, Arkadiusz Sitek:
MISS: Multiclass Interpretable Scoring Systems. SDM 2024: 55-63 - [c67]Monika Wysoczanska, Michaël Ramamonjisoa, Tomasz Trzcinski, Oriane Siméoni:
CLIP-DIY: CLIP Dense Inference Yields Open-Vocabulary Semantic Segmentation For-Free. WACV 2024: 1392-1402 - [c66]Filip Szatkowski, Mateusz Pyla, Marcin Przewiezlikowski, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski:
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning. WACV 2024: 1966-1976 - [c65]Jan Dubinski, Antoni Kowalczuk, Stanislaw Pawlak, Przemyslaw Rokita, Tomasz Trzcinski, Pawel Morawiecki:
Towards More Realistic Membership Inference Attacks on Large Diffusion Models. WACV 2024: 4848-4857 - 2023
- [c64]Kacper Kania, Stephan J. Garbin, Andrea Tagliasacchi, Virginia Estellers, Kwang Moo Yi, Julien Valentin, Tomasz Trzcinski, Marek Kowalski:
BlendFields: Few-Shot Example-Driven Facial Modeling. CVPR 2023: 404-415 - [c63]Damian Sójka, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski:
AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation. ICCV (Workshops) 2023: 3483-3487 - [c62]Valeriya Khan, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski:
Looking through the past: better knowledge retention for generative replay in continual learning. ICCV (Workshops) 2023: 3488-3492 - [c61]Filip Szatkowski, Mateusz Pyla, Marcin Przewiezlikowski, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski:
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning. ICCV (Workshops) 2023: 3504-3509 - [c60]Adam Pardyl, Grzegorz Rypesc, Grzegorz Kurzejamski, Bartosz Zielinski, Tomasz Trzcinski:
Active Visual Exploration Based on Attention-Map Entropy. IJCAI 2023: 1303-1311 - [c59]Michal K. Grzeszczyk, Szymon Plotka, Beata Rebizant, Katarzyna Kosinska-Kaczynska, Michal Lipa, Robert Brawura-Biskupski-Samaha, Przemyslaw Korzeniowski, Tomasz Trzcinski, Arkadiusz Sitek:
TabAttention: Learning Attention Conditionally on Tabular Data. MICCAI (7) 2023: 347-357 - [c58]Jan Dubinski, Stanislaw Pawlak, Franziska Boenisch, Tomasz Trzcinski, Adam Dziedzic:
Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders. NeurIPS 2023 - [c57]Wojciech Masarczyk, Mateusz Ostaszewski, Ehsan Imani, Razvan Pascanu, Piotr Milos, Tomasz Trzcinski:
The Tunnel Effect: Building Data Representations in Deep Neural Networks. NeurIPS 2023 - [c56]Kamil Deja, Tomasz Trzcinski, Jakub M. Tomczak:
Learning Data Representations with Joint Diffusion Models. ECML/PKDD (2) 2023: 543-559 - [c55]Filip Szatkowski, Karol J. Piczak, Przemyslaw Spurek, Jacek Tabor, Tomasz Trzcinski:
Hypernetworks Build Implicit Neural Representations of Sounds. ECML/PKDD (4) 2023: 661-676 - 2022
- [c54]Anna Wróblewska, Jozef Jasek, Bogdan Jastrzebski, Stanislaw Pawlak, Anna Grzywacz, Siew Ann Cheong, Seng Chee Tan, Tomasz Trzcinski, Janusz A. Holyst:
Deep Learning for Automatic Detection of Qualitative Features of Lecturing. AIED (1) 2022: 698-703 - [c53]Kacper Kania, Kwang Moo Yi, Marek Kowalski, Tomasz Trzcinski, Andrea Tagliasacchi:
CoNeRF: Controllable Neural Radiance Fields. CVPR 2022: 18602-18611 - [c52]Michal K. Grzeszczyk, Tadeusz Satlawa, Angela Lungu, Andrew J. Swift, Andrew J. Narracott, D. Rodney Hose, Tomasz Trzcinski, Arkadiusz Sitek:
Noninvasive Estimation of Mean Pulmonary Artery Pressure Using MRI, Computer Models, and Machine Learning. ICCS (3) 2022: 14-27 - [c51]Tomasz Smierzchalski, Lukasz Pawela, Zbigniew Puchala, Tomasz Trzcinski, Bartlomiej Gardas:
Post-error Correction for Quantum Annealing Processor Using Reinforcement Learning. ICCS (4) 2022: 261-268 - [c50]Witold Oleszkiewicz, Dominika Basaj, Tomasz Trzcinski, Bartosz Zielinski:
Which Visual Features Impact the Performance of Target Task in Self-supervised Learning? ICCS (1) 2022: 331-344 - [c49]Tomasz Szczepanski, Arkadiusz Sitek, Tomasz Trzcinski, Szymon Plotka:
POTHER: Patch-Voted Deep Learning-Based Chest X-ray Bias Analysis for COVID-19 Detection. ICCS (1) 2022: 441-454 - [c48]Maciej Wolczyk, Karol J. Piczak, Bartosz Wójcik, Lukasz Pustelnik, Pawel Morawiecki, Jacek Tabor, Tomasz Trzcinski, Przemyslaw Spurek:
Continual Learning with Guarantees via Weight Interval Constraints. ICML 2022: 23897-23911 - [c47]Jan Dubinski, Kamil Deja, Sandro Wenzel, Przemyslaw Rokita, Tomasz Trzcinski:
Selectively Increasing the Diversity of GAN-Generated Samples. ICONIP (1) 2022: 260-270 - [c46]Stanislaw Pawlak, Filip Szatkowski, Michal Bortkiewicz, Jan Dubinski, Tomasz Trzcinski:
Progressive Latent Replay for Efficient Generative Rehearsal. ICONIP (4) 2022: 457-467 - [c45]Kamil Deja, Pawel Wawrzynski, Wojciech Masarczyk, Daniel Marczak, Tomasz Trzcinski:
Multiband VAE: Latent Space Alignment for Knowledge Consolidation in Continual Learning. IJCAI 2022: 2902-2908 - [c44]Przemyslaw Spurek, Artur Kasymov, Marcin Mazur, Diana Janik, Slawomir Konrad Tadeja, Lukasz Struski, Jacek Tabor, Tomasz Trzcinski:
HyperPocket: Generative Point Cloud Completion. IROS 2022: 6848-6853 - [c43]Szymon Plotka, Michal K. Grzeszczyk, Robert Brawura-Biskupski-Samaha, Pawel Gutaj, Michal Lipa, Tomasz Trzcinski, Arkadiusz Sitek:
BabyNet: Residual Transformer Module for Birth Weight Prediction on Fetal Ultrasound Video. MICCAI (4) 2022: 350-359 - [c42]Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub M. Tomczak:
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models. NeurIPS 2022 - [c41]Pawel Lorek, Rafal Nowak, Tomasz Trzcinski, Maciej Zieba:
FlowHMM: Flow-based continuous hidden Markov models. NeurIPS 2022 - 2021
- [c40]Szymon Plotka, Tomasz Wlodarczyk, Adam Klasa, Michal Lipa, Arkadiusz Sitek, Tomasz Trzcinski:
FetalNet: Multi-task Deep Learning Framework for Fetal Ultrasound Biometric Measurements. ICONIP (6) 2021: 257-265 - [c39]Ivona Tautkute, Tomasz Trzcinski:
SynthTriplet GAN: Synthetic Query Expansion for Multimodal Retrieval. ICONIP (4) 2021: 287-298 - [c38]Wojciech Masarczyk, Kamil Deja, Tomasz Trzcinski:
On Robustness of Generative Representations Against Catastrophic Forgetting. ICONIP (6) 2021: 325-333 - [c37]Michal Sadowski, Karol J. Piczak, Przemyslaw Spurek, Tomasz Trzcinski:
Continual Learning of 3D Point Cloud Generators. ICONIP (1) 2021: 330-341 - [c36]Jacek Komorowski, Monika Wysoczanska, Tomasz Trzcinski:
Large-Scale Topological Radar Localization Using Learned Descriptors. ICONIP (2) 2021: 451-462 - [c35]Dominika Basaj, Witold Oleszkiewicz, Igor Sieradzki, Michal Górszczak, Barbara Rychalska, Tomasz Trzcinski, Bartosz Zielinski:
Explaining Self-Supervised Image Representations with Visual Probing. IJCAI 2021: 592-598 - [c34]Kamil Deja, Pawel Wawrzynski, Daniel Marczak, Wojciech Masarczyk, Tomasz Trzcinski:
BinPlay: A Binary Latent Autoencoder for Generative Replay Continual Learning. IJCNN 2021: 1-8 - [c33]Jacek Komorowski, Monika Wysoczanska, Tomasz Trzcinski:
MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition. IJCNN 2021: 1-8 - [c32]Maciej Wolczyk, Bartosz Wójcik, Klaudia Balazy, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski:
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks. NeurIPS 2021: 2516-2528 - [c31]Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Tomasz Trzcinski, Przemyslaw Spurek, Maciej Zieba:
Non-Gaussian Gaussian Processes for Few-Shot Regression. NeurIPS 2021: 10285-10298 - [c30]Jacek Komorowski, Grzegorz Kurzejamski, Monika Wysoczanska, Tomasz Trzcinski:
Global Point Cloud Descriptor for Place Recognition in Indoor Environments. VISIGRAPP (5: VISAPP) 2021: 216-224 - 2020
- [c29]Grzegorz Kurzejamski, Jacek Komorowski, Lukasz Dabala, Konrad Czarnota, Simon Lynen, Tomasz Trzcinski:
SuperNCN: Neighbourhood Consensus Network for Robust Outdoor Scenes Matching. ACIVS 2020: 492-503 - [c28]Przemyslaw Spurek, Sebastian Winczowski, Jacek Tabor, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski:
Hypernetwork approach to generating point clouds. ICML 2020: 9099-9108 - [c27]Tomasz Trzcinski:
Comixify: turning videos into comics. AI4Narratives@IJCAI 2020: 3 - [c26]Tomasz Wlodarczyk, Szymon Plotka, Przemyslaw Rokita, Nicole Sochacki-Wójcicka, Jakub Wójcicki, Michal Lipa, Tomasz Trzcinski:
Spontaneous Preterm Birth Prediction Using Convolutional Neural Networks. ASMUS/PIPPI@MICCAI 2020: 274-283 - [c25]Monika Wysoczanska, Tomasz Trzcinski:
Multimodal Dance Recognition. VISIGRAPP (5: VISAPP) 2020: 558-565 - [c24]Michal Koperski, Tomasz K. Konopczynski, Rafal Nowak, Piotr Semberecki, Tomasz Trzcinski:
Plugin Networks for Inference under Partial Evidence. WACV 2020: 2872-2880 - 2019
- [c23]Piotr Woznicki, Przemyslaw Przybyszewski, Norbert Kapinski, Jakub Zielinski, Beata Ciszkowska-Lyson, Bartosz A. Borucki, Tomasz Trzcinski, Krzysztof Nowinski:
Monitoring Achilles Tendon Healing Progress in Ultrasound Imaging with Convolutional Neural Networks. SUSI/PIPPI@MICCAI 2019: 65-73 - [c22]Tomasz Wlodarczyk, Szymon Plotka, Tomasz Trzcinski, Przemyslaw Rokita, Nicole Sochacki-Wójcicka, Michal Lipa, Jakub Wójcicki:
Estimation of Preterm Birth Markers with U-Net Segmentation Network. SUSI/PIPPI@MICCAI 2019: 95-103 - 2018
- [c21]Witold Oleszkiewicz, Peter Kairouz, Karol J. Piczak, Ram Rajagopal, Tomasz Trzcinski:
Siamese Generative Adversarial Privatizer for Biometric Data. ACCV (5) 2018: 482-497 - [c20]Ivona Tautkute, Tomasz Trzcinski, Adam Bielski:
Recognizing Emotions with EmotionalDAN. CompIMAGE 2018: 120-128 - [c19]Ivona Tautkute, Tomasz Trzcinski, Adam Bielski:
I Know How You Feel: Emotion Recognition With Facial Landmarks. CVPR Workshops 2018: 1878-1880 - [c18]Adam Bielski, Tomasz Trzcinski:
Pay Attention to Virality: Understanding Popularity of Social Media Videos With the Attention Mechanism. CVPR Workshops 2018: 2335-2337 - [c17]Tomasz Trzcinski, Jacek Komorowski, Lukasz Dabala, Konrad Czarnota, Grzegorz Kurzejamski, Simon Lynen:
SConE: Siamese Constellation Embedding Descriptor for Image Matching. ECCV Workshops (1) 2018: 401-413 - [c16]Jacek Komorowski, Konrad Czarnota, Tomasz Trzcinski, Lukasz Dabala, Simon Lynen:
Interest Point Detectors Stability Evaluation on ApolloScape Dataset. ECCV Workshops (5) 2018: 727-739 - [c15]Adam Slucki, Tomasz Trzcinski, Adam Bielski, Pawel Cyrta:
Extracting Textual Overlays from Social Media Videos Using Neural Networks. ICCVG 2018: 287-299 - [c14]Jacek Komorowski, Tomasz Trzcinski:
Aggregation of Binary Feature Descriptors for Compact Scene Model Representation in Large Scale Structure-from-Motion Applications. ICCVG 2018: 363-374 - [c13]Norbert Kapinski, Jakub Zielinski, Bartosz A. Borucki, Tomasz Trzcinski, Beata Ciszkowska-Lyson, Krzysztof S. Nowinski:
Estimating Achilles Tendon Healing Progress with Convolutional Neural Networks. MICCAI (2) 2018: 949-957 - [c12]Maciej Zieba, Piotr Semberecki, Tarek El-Gaaly, Tomasz Trzcinski:
BinGAN: Learning Compact Binary Descriptors with a Regularized GAN. NeurIPS 2018: 3612-3622 - 2017
- [c11]Marek Kowalski, Jacek Naruniec, Tomasz Trzcinski:
Deep Alignment Network: A Convolutional Neural Network for Robust Face Alignment. CVPR Workshops 2017: 2034-2043 - [c10]Ivona Tautkute, Aleksandra Mozejko, Wojciech Stokowiec, Tomasz Trzcinski, Lukasz Brocki, Krzysztof Marasek:
What Looks Good with my Sofa: Ensemble Multimodal Search for Interior Design. FedCSIS 2017: 1275-1282 - [c9]Jacek Komorowski, Tomasz Trzcinski:
Evaluation of Hashing Methods Performance on Binary Feature Descriptors. IP&C 2017: 88-98 - [c8]Pawel Cyrta, Tomasz Trzcinski, Wojciech Stokowiec:
Speaker Diarization Using Deep Recurrent Convolutional Neural Networks for Speaker Embeddings. ISAT (1) 2017: 107-117 - [c7]Wojciech Stokowiec, Tomasz Trzcinski, Krzysztof Wolk, Krzysztof Marasek, Przemyslaw Rokita:
Shallow Reading with Deep Learning: Predicting Popularity of Online Content Using only Its Title. ISMIS 2017: 136-145 - [c6]Tomasz Trzcinski, Pawel Andruszkiewicz, Tomasz Bochenski, Przemyslaw Rokita:
Recurrent Neural Networks for Online Video Popularity Prediction. ISMIS 2017: 146-153 - [c5]Michal Komorowski, Tomasz Trzcinski:
Random Binary Search Trees for Approximate Nearest Neighbour Search in Binary Space. PReMI 2017: 473-479 - [c4]Maciej Suchecki, Tomasz Trzcinski:
Understanding aesthetics in photography using deep convolutional neural networks. SPA 2017: 149-153 - 2013
- [c3]Tomasz Trzcinski, C. Mario Christoudias, Pascal Fua, Vincent Lepetit:
Boosting Binary Keypoint Descriptors. CVPR 2013: 2874-2881 - 2012
- [c2]Tomasz Trzcinski, Vincent Lepetit:
Efficient Discriminative Projections for Compact Binary Descriptors. ECCV (1) 2012: 228-242 - [c1]Tomasz Trzcinski, C. Mario Christoudias, Vincent Lepetit, Pascal Fua:
Learning Image Descriptors with the Boosting-Trick. NIPS 2012: 278-286
Informal and Other Publications
- 2024
- [i105]Michal K. Grzeszczyk, Tomasz Trzcinski, Arkadiusz Sitek:
MISS: Multiclass Interpretable Scoring Systems. CoRR abs/2401.05069 (2024) - [i104]Grzegorz Rypesc, Sebastian Cygert, Valeriya Khan, Tomasz Trzcinski, Bartosz Zielinski, Bartlomiej Twardowski:
Divide and not forget: Ensemble of selectively trained experts in Continual Learning. CoRR abs/2401.10191 (2024) - [i103]Michal Nauman, Michal Bortkiewicz, Mateusz Ostaszewski, Piotr Milos, Tomasz Trzcinski, Marek Cygan:
Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning. CoRR abs/2403.00514 (2024) - [i102]Bartosz Cywinski, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski, Lukasz Kucinski:
GUIDE: Guidance-based Incremental Learning with Diffusion Models. CoRR abs/2403.03938 (2024) - [i101]Filip Szatkowski, Fei Yang, Bartlomiej Twardowski, Tomasz Trzcinski, Joost van de Weijer:
Accelerated Inference and Reduced Forgetting: The Dual Benefits of Early-Exit Networks in Continual Learning. CoRR abs/2403.07404 (2024) - [i100]Adam Pardyl, Michal Wronka, Maciej Wolczyk, Kamil Adamczewski, Tomasz Trzcinski, Bartosz Zielinski:
AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale. CoRR abs/2404.03482 (2024) - [i99]Monika Wysoczanska, Antonín Vobecký, Amaia Cardiel, Tomasz Trzcinski, Renaud Marlet, Andrei Bursuc, Oriane Siméoni:
A Study of Test-time Contrastive Concepts for Open-world, Open-vocabulary Semantic Segmentation. CoRR abs/2407.05061 (2024) - [i98]Daniel Marczak, Bartlomiej Twardowski, Tomasz Trzcinski, Sebastian Cygert:
MagMax: Leveraging Model Merging for Seamless Continual Learning. CoRR abs/2407.06322 (2024) - [i97]Tomasz Szczepanski, Michal K. Grzeszczyk, Szymon Plotka, Arleta Adamowicz, Piotr Fudalej, Przemyslaw Korzeniowski, Tomasz Trzcinski, Arkadiusz Sitek:
Let Me DeCode You: Decoder Conditioning with Tabular Data. CoRR abs/2407.09437 (2024) - [i96]Sebastian Cygert, Damian Sójka, Tomasz Trzcinski, Bartlomiej Twardowski:
Realistic Evaluation of Test-Time Adaptation Algorithms: Unsupervised Hyperparameter Selection. CoRR abs/2407.14231 (2024) - [i95]Bartlomiej Krzepkowski, Monika Michaluk, Franciszek Szarwacki, Piotr Kubaty, Jary Pomponi, Tomasz Trzcinski, Bartosz Wójcik, Kamil Adamczewski:
Joint or Disjoint: Mixing Training Regimes for Early-Exit Models. CoRR abs/2407.14320 (2024) - [i94]Joanna Kaleta, Kacper Kania, Tomasz Trzcinski, Marek Kowalski:
LumiGauss: High-Fidelity Outdoor Relighting with 2D Gaussian Splatting. CoRR abs/2408.04474 (2024) - [i93]Michal K. Grzeszczyk, Przemyslaw Korzeniowski, Samer Alabed, Andrew J. Swift, Tomasz Trzcinski, Arkadiusz Sitek:
TabMixer: Noninvasive Estimation of the Mean Pulmonary Artery Pressure via Imaging and Tabular Data Mixing. CoRR abs/2409.07564 (2024) - [i92]Grzegorz Rypesc, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski:
Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning. CoRR abs/2409.18265 (2024) - 2023
- [i91]Kamil Deja, Tomasz Trzcinski, Jakub M. Tomczak:
Learning Data Representations with Joint Diffusion Models. CoRR abs/2301.13622 (2023) - [i90]Michal K. Grzeszczyk, Paulina Adamczyk, Sylwia Marek, Ryszard Precikowski, Maciej Kus, M. Patrycja Lelujko, Rosmary Blanco, Tomasz Trzcinski, Arkadiusz Sitek, Maciej Malawski, Aneta Lisowska:
Can gamification reduce the burden of self-reporting in mHealth applications? Feasibility study using machine learning from smartwatch data to estimate cognitive load. CoRR abs/2302.03616 (2023) - [i89]Filip Szatkowski, Karol J. Piczak, Przemyslaw Spurek, Jacek Tabor, Tomasz Trzcinski:
Hypernetworks build Implicit Neural Representations of Sounds. CoRR abs/2302.04959 (2023) - [i88]Adam Pardyl, Grzegorz Rypesc, Grzegorz Kurzejamski, Bartosz Zielinski, Tomasz Trzcinski:
Active Visual Exploration Based on Attention-Map Entropy. CoRR abs/2303.06457 (2023) - [i87]Michal Zajac, Kamil Deja, Anna Kuzina, Jakub M. Tomczak, Tomasz Trzcinski, Florian Shkurti, Piotr Milos:
Exploring Continual Learning of Diffusion Models. CoRR abs/2303.15342 (2023) - [i86]Kacper Kania, Stephan J. Garbin, Andrea Tagliasacchi, Virginia Estellers, Kwang Moo Yi, Julien Valentin, Tomasz Trzcinski, Marek Kowalski:
BlendFields: Few-Shot Example-Driven Facial Modeling. CoRR abs/2305.07514 (2023) - [i85]Wojciech Masarczyk, Mateusz Ostaszewski, Ehsan Imani, Razvan Pascanu, Piotr Milos, Tomasz Trzcinski:
The Tunnel Effect: Building Data Representations in Deep Neural Networks. CoRR abs/2305.19753 (2023) - [i84]Jan Dubinski, Antoni Kowalczuk, Stanislaw Pawlak, Przemyslaw Rokita, Tomasz Trzcinski, Pawel Morawiecki:
Towards More Realistic Membership Inference Attacks on Large Diffusion Models. CoRR abs/2306.12983 (2023) - [i83]Jan Dubinski, Kamil Deja, Sandro Wenzel, Przemyslaw Rokita, Tomasz Trzcinski:
Machine Learning methods for simulating particle response in the Zero Degree Calorimeter at the ALICE experiment, CERN. CoRR abs/2306.13606 (2023) - [i82]Filip Szatkowski, Mateusz Pyla, Marcin Przewiezlikowski, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski:
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning. CoRR abs/2308.09544 (2023) - [i81]Daniel Marczak, Grzegorz Rypesc, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski:
Generalized Continual Category Discovery. CoRR abs/2308.12112 (2023) - [i80]Valeriya Khan, Sebastian Cygert, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski:
Looking through the past: better knowledge retention for generative replay in continual learning. CoRR abs/2309.10012 (2023) - [i79]Damian Sójka, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski:
AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation. CoRR abs/2309.10109 (2023) - [i78]Adam Pardyl, Grzegorz Kurzejamski, Jan Olszewski, Tomasz Trzcinski, Bartosz Zielinski:
Beyond Grids: Exploring Elastic Input Sampling for Vision Transformers. CoRR abs/2309.13353 (2023) - [i77]Monika Wysoczanska, Michaël Ramamonjisoa, Tomasz Trzcinski, Oriane Siméoni:
CLIP-DIY: CLIP Dense Inference Yields Open-Vocabulary Semantic Segmentation For-Free. CoRR abs/2309.14289 (2023) - [i76]Jan Dubinski, Stanislaw Pawlak, Franziska Boenisch, Tomasz Trzcinski, Adam Dziedzic:
Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders. CoRR abs/2310.08571 (2023) - [i75]Mateusz Pyla, Kamil Deja, Bartlomiej Twardowski, Tomasz Trzcinski:
Bayesian Flow Networks in Continual Learning. CoRR abs/2310.12001 (2023) - [i74]Wojciech Masarczyk, Tomasz Trzcinski, Mateusz Ostaszewski:
On consequences of finetuning on data with highly discriminative features. CoRR abs/2310.19537 (2023) - [i73]Daniel Marczak, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski:
Revisiting Supervision for Continual Representation Learning. CoRR abs/2311.13321 (2023) - [i72]Monika Wysoczanska, Oriane Siméoni, Michaël Ramamonjisoa, Andrei Bursuc, Tomasz Trzcinski, Patrick Pérez:
CLIP-DINOiser: Teaching CLIP a few DINO tricks. CoRR abs/2312.12359 (2023) - [i71]Kamil Deja, Bartosz Cywinski, Jan Rybarczyk, Tomasz Trzcinski:
Adapt & Align: Continual Learning with Generative Models Latent Space Alignment. CoRR abs/2312.13699 (2023) - [i70]Michal K. Grzeszczyk, Tadeusz Satlawa, Angela Lungu, Andrew J. Swift, Andrew J. Narracott, Rod Hose, Tomasz Trzcinski, Arkadiusz Sitek:
Noninvasive Estimation of Mean Pulmonary Artery Pressure Using MRI, Computer Models, and Machine Learning. CoRR abs/2312.14221 (2023) - [i69]Sebastian Dziadzio, Çagatay Yildiz, Gido M. van de Ven, Tomasz Trzcinski, Tinne Tuytelaars, Matthias Bethge:
Disentangled Continual Learning: Separating Memory Edits from Model Updates. CoRR abs/2312.16731 (2023) - 2022
- [i68]Wojciech Masarczyk, Pawel Wawrzynski, Daniel Marczak, Kamil Deja, Tomasz Trzcinski:
Logarithmic Continual Learning. CoRR abs/2201.06534 (2022) - [i67]Tomasz Szczepanski, Arkadiusz Sitek, Tomasz Trzcinski, Szymon Plotka:
POTHER: Patch-Voted Deep Learning-based Chest X-ray Bias Analysis for COVID-19 Detection. CoRR abs/2201.09360 (2022) - [i66]Maciej Zamorski, Michal Stypulkowski, Konrad Karanowski, Tomasz Trzcinski, Maciej Zieba:
Continual learning on 3D point clouds with random compressed rehearsal. CoRR abs/2205.08013 (2022) - [i65]Szymon Plotka, Michal K. Grzeszczyk, Robert Brawura-Biskupski-Samaha, Pawel Gutaj, Michal Lipa, Tomasz Trzcinski, Arkadiusz Sitek:
BabyNet: Residual Transformer Module for Birth Weight Prediction on Fetal Ultrasound Video. CoRR abs/2205.09382 (2022) - [i64]Szymon Plotka, Adam Klasa, Aneta Lisowska, Joanna Seliga-Siwecka, Michal Lipa, Tomasz Trzcinski, Arkadiusz Sitek:
Deep Learning Fetal Ultrasound Video Model Match Human Observers in Biometric Measurements. CoRR abs/2205.13835 (2022) - [i63]Anna Wróblewska, Jozef Jasek, Bogdan Jastrzebski, Stanislaw Pawlak, Anna Grzywacz, Siew Ann Cheong, Tan Seng Chee, Tomasz Trzcinski, Janusz A. Holyst:
A Deep Learning Approach for Automatic Detection of Qualitative Features of Lecturing. CoRR abs/2205.14919 (2022) - [i62]Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub M. Tomczak:
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models. CoRR abs/2206.00070 (2022) - [i61]Dominik Zimny, Tomasz Trzcinski, Przemyslaw Spurek:
Points2NeRF: Generating Neural Radiance Fields from 3D point cloud. CoRR abs/2206.01290 (2022) - [i60]Maciej Wolczyk, Karol J. Piczak, Bartosz Wójcik, Lukasz Pustelnik, Pawel Morawiecki, Jacek Tabor, Tomasz Trzcinski, Przemyslaw Spurek:
Continual Learning with Guarantees via Weight Interval Constraints. CoRR abs/2206.07996 (2022) - [i59]Jan Dubinski, Kamil Deja, Sandro Wenzel, Przemyslaw Rokita, Tomasz Trzcinski:
Selectively increasing the diversity of GAN-generated samples. CoRR abs/2207.01561 (2022) - [i58]Stanislaw Pawlak, Filip Szatkowski, Michal Bortkiewicz, Jan Dubinski, Tomasz Trzcinski:
Progressive Latent Replay for efficient Generative Rehearsal. CoRR abs/2207.01562 (2022) - [i57]Filip Szatkowski, Karol J. Piczak, Przemyslaw Spurek, Jacek Tabor, Tomasz Trzcinski:
HyperSound: Generating Implicit Neural Representations of Audio Signals with Hypernetworks. CoRR abs/2211.01839 (2022) - [i56]Michal Bortkiewicz, Jakub Lyskawa, Pawel Wawrzynski, Mateusz Ostaszewski, Artur Grudkowski, Tomasz Trzcinski:
Emergency action termination for immediate reaction in hierarchical reinforcement learning. CoRR abs/2211.06351 (2022) - [i55]Monika Wysoczanska, Tom Monnier, Tomasz Trzcinski, David Picard:
Towards Unsupervised Visual Reasoning: Do Off-The-Shelf Features Know How to Reason? CoRR abs/2212.10292 (2022) - 2021
- [i54]Przemyslaw Spurek, Artur Kasymov, Marcin Mazur, Diana Janik, Slawomir Konrad Tadeja, Lukasz Struski, Jacek Tabor, Tomasz Trzcinski:
HyperPocket: Generative Point Cloud Completion. CoRR abs/2102.05973 (2021) - [i53]Przemyslaw Spurek, Sebastian Winczowski, Maciej Zieba, Tomasz Trzcinski, Kacper Kania:
Modeling 3D Surface Manifolds with a Locally Conditioned Atlas. CoRR abs/2102.05984 (2021) - [i52]Kacper Kania, Marek Kowalski, Tomasz Trzcinski:
TrajeVAE - Controllable Human Motion Generation from Trajectories. CoRR abs/2104.00351 (2021) - [i51]Jacek Komorowski, Monika Wysoczanska, Tomasz Trzcinski:
MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition. CoRR abs/2104.05327 (2021) - [i50]Szymon Plotka, Tomasz Wlodarczyk, Ryszard Szczerba, Przemyslaw Rokita, Patrycja Bartkowska, Oskar Komisarek, Artur Matthews-Brzozowski, Tomasz Trzcinski:
Convolutional Neural Networks in Orthodontics: a review. CoRR abs/2104.08886 (2021) - [i49]Maciej Wolczyk, Bartosz Wójcik, Klaudia Balazy, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski:
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks. CoRR abs/2106.05409 (2021) - [i48]Witold Oleszkiewicz, Dominika Basaj, Igor Sieradzki, Michal Górszczak, Barbara Rychalska, Koryna Lewandowska, Tomasz Trzcinski, Bartosz Zielinski:
Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations. CoRR abs/2106.11054 (2021) - [i47]Kamil Deja, Pawel Wawrzynski, Daniel Marczak, Wojciech Masarczyk, Tomasz Trzcinski:
Multiband VAE: Latent Space Partitioning for Knowledge Consolidation in Continual Learning. CoRR abs/2106.12196 (2021) - [i46]Szymon Plotka, Tomasz Wlodarczyk, Adam Klasa, Michal Lipa, Arkadiusz Sitek, Tomasz Trzcinski:
FetalNet: Multi-task deep learning framework for fetal ultrasound biometric measurements. CoRR abs/2107.06943 (2021) - [i45]Ivan Kostiuk, Przemyslaw Stachura, Slawomir Konrad Tadeja, Tomasz Trzcinski, Przemyslaw Spurek:
HyperColor: A HyperNetwork Approach for Synthesizing Auto-colored 3D Models for Game Scenes Population. CoRR abs/2108.01411 (2021) - [i44]Wojciech Masarczyk, Kamil Deja, Tomasz Trzcinski:
On robustness of generative representations against catastrophic forgetting. CoRR abs/2109.01844 (2021) - [i43]Jacek Komorowski, Monika Wysoczanska, Tomasz Trzcinski:
Large-Scale Topological Radar Localization Using Learned Descriptors. CoRR abs/2110.03081 (2021) - [i42]Lukasz Struski, Pawel M. Morkisz, Przemyslaw Spurek, Samuel Rodriguez Bernabeu, Tomasz Trzcinski:
Efficient GPU implementation of randomized SVD and its applications. CoRR abs/2110.03423 (2021) - [i41]Magdalena Proszewska, Marcin Mazur, Tomasz Trzcinski, Przemyslaw Spurek:
HyperCube: Implicit Field Representations of Voxelized 3D Models. CoRR abs/2110.05770 (2021) - [i40]Jacek Komorowski, Monika Wysoczanska, Tomasz Trzcinski:
EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale. CoRR abs/2110.12486 (2021) - [i39]Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Tomasz Trzcinski, Przemyslaw Spurek, Maciej Zieba:
Non-Gaussian Gaussian Processes for Few-Shot Regression. CoRR abs/2110.13561 (2021) - [i38]Kacper Kania, Kwang Moo Yi, Marek Kowalski, Tomasz Trzcinski, Andrea Tagliasacchi:
CoNeRF: Controllable Neural Radiance Fields. CoRR abs/2112.01983 (2021) - 2020
- [i37]Przemyslaw Spurek, Sebastian Winczowski, Jacek Tabor, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski:
Hypernetwork approach to generating point clouds. CoRR abs/2003.00802 (2020) - [i36]Witold Oleszkiewicz, Taro Makino, Stanislaw Jastrzebski, Tomasz Trzcinski, Linda Moy, Kyunghyun Cho, Laura Heacock, Krzysztof J. Geras:
Understanding the robustness of deep neural network classifiers for breast cancer screening. CoRR abs/2003.10041 (2020) - [i35]Kamil Deja, Jan Dubinski, Piotr Nowak, Sandro Wenzel, Tomasz Trzcinski:
End-to-end Sinkhorn Autoencoder with Noise Generator. CoRR abs/2006.06704 (2020) - [i34]Przemyslaw Spurek, Maciej Zieba, Jacek Tabor, Tomasz Trzcinski:
HyperFlow: Representing 3D Objects as Surfaces. CoRR abs/2006.08710 (2020) - [i33]Tomasz Wlodarczyk, Szymon Plotka, Przemyslaw Rokita, Nicole Sochacki-Wójcicka, Jakub Wójcicki, Michal Lipa, Tomasz Trzcinski:
Spontaneous preterm birth prediction using convolutional neural networks. CoRR abs/2008.07000 (2020) - [i32]Michal Stypulkowski, Kacper Kania, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski, Jan Chorowski:
Representing Point Clouds with Generative Conditional Invertible Flow Networks. CoRR abs/2010.11087 (2020) - [i31]Maciej Zieba, Marcin Przewiezlikowski, Marek Smieja, Jacek Tabor, Tomasz Trzcinski, Przemyslaw Spurek:
RegFlow: Probabilistic Flow-based Regression for Future Prediction. CoRR abs/2011.14620 (2020) - [i30]Kamil Deja, Pawel Wawrzynski, Daniel Marczak, Wojciech Masarczyk, Tomasz Trzcinski:
BinPlay: A Binary Latent Autoencoder for Generative Replay Continual Learning. CoRR abs/2011.14960 (2020) - 2019
- [i29]Michal Koperski, Tomasz K. Konopczynski, Piotr Semberecki, Tomasz Trzcinski:
Plugin Networks for Inference under Partial Evidence. CoRR abs/1901.00326 (2019) - [i28]Tomasz Wlodarczyk, Szymon Plotka, Tomasz Trzcinski, Przemyslaw Rokita, Nicole Sochacki-Wójcicka, Michal Lipa, Jakub Wójcicki:
Estimation of preterm birth markers with U-Net segmentation network. CoRR abs/1908.09148 (2019) - [i27]Piotr Woznicki, Przemyslaw Przybyszewski, Norbert Kapinski, Jakub Zielinski, Beata Ciszkowska-Lyson, Bartosz A. Borucki, Tomasz Trzcinski, Krzysztof S. Nowinski:
Monitoring Achilles tendon healing progress in ultrasound imaging with convolutional neural networks. CoRR abs/1909.04973 (2019) - [i26]Norbert Kapinski, Jedrzej M. Nowosielski, Maciej E. Marchwiany, Jakub Zielinski, Beata Ciszkowska-Lyson, Bartosz A. Borucki, Tomasz Trzcinski, Krzysztof S. Nowinski:
Late fusion of deep learning and hand-crafted features for Achilles tendon healing monitoring. CoRR abs/1909.05687 (2019) - [i25]Grzegorz Kurzejamski, Jacek Komorowski, Lukasz Dabala, Konrad Czarnota, Simon Lynen, Tomasz Trzcinski:
SuperNCN: Neighbourhood consensus network for robust outdoor scenes matching. CoRR abs/1912.04627 (2019) - 2018
- [i24]Ivona Tautkute, Tomasz Trzcinski, Aleksander Skorupa, Lukasz Brocki, Krzysztof Marasek:
DeepStyle: Multimodal Search Engine for Fashion and Interior Design. CoRR abs/1801.03002 (2018) - [i23]Tomasz Trzcinski, Adam Bielski, Pawel Cyrta, Matthew Zak:
SocialML: machine learning for social media video creators. CoRR abs/1802.02204 (2018) - [i22]Witold Oleszkiewicz, Tomasz Wlodarczyk, Karol J. Piczak, Tomasz Trzcinski, Peter Kairouz, Ram Rajagopal:
Siamese Generative Adversarial Privatizer for Biometric Data. CoRR abs/1804.08757 (2018) - [i21]Adam Bielski, Tomasz Trzcinski:
Pay Attention to Virality: understanding popularity of social media videos with the attention mechanism. CoRR abs/1804.09949 (2018) - [i20]Adam Slucki, Tomasz Trzcinski, Adam Bielski, Pawel Cyrta:
Extracting textual overlays from social media videos using neural networks. CoRR abs/1804.10687 (2018) - [i19]Ivona Tautkute, Tomasz Trzcinski, Adam Bielski:
I Know How You Feel: Emotion Recognition with Facial Landmarks. CoRR abs/1805.00326 (2018) - [i18]Norbert Kapinski, Jakub Zielinski, Bartosz A. Borucki, Tomasz Trzcinski, Beata Ciszkowska-Lyson, Krzysztof S. Nowinski:
Estimating Achilles tendon healing progress with convolutional neural networks. CoRR abs/1806.05091 (2018) - [i17]Maciej Zieba, Piotr Semberecki, Tarek El-Gaaly, Tomasz Trzcinski:
BinGAN: Learning Compact Binary Descriptors with a Regularized GAN. CoRR abs/1806.06778 (2018) - [i16]Maciej Pesko, Tomasz Trzcinski:
Neural Comic Style Transfer: Case Study. CoRR abs/1809.01726 (2018) - [i15]Jacek Komorowski, Konrad Czarnota, Tomasz Trzcinski, Lukasz Dabala, Simon Lynen:
Interest point detectors stability evaluation on ApolloScape dataset. CoRR abs/1809.11039 (2018) - [i14]Tomasz Trzcinski, Jacek Komorowski, Lukasz Dabala, Konrad Czarnota, Grzegorz Kurzejamski, Simon Lynen:
SConE: Siamese Constellation Embedding Descriptor for Image Matching. CoRR abs/1809.11054 (2018) - [i13]Jacek Komorowski, Tomasz Trzcinski:
Aggregation of binary feature descriptors for compact scene model representation in large scale structure-from-motion applications. CoRR abs/1809.11062 (2018) - [i12]Ivona Tautkute, Tomasz Trzcinski:
Classifying and Visualizing Emotions with Emotional DAN. CoRR abs/1810.10529 (2018) - [i11]Maciej Zamorski, Maciej Zieba, Rafal Nowak, Wojciech Stokowiec, Tomasz Trzcinski:
Adversarial Autoencoders for Generating 3D Point Clouds. CoRR abs/1811.07605 (2018) - [i10]Maciej Pesko, Adam Svystun, Pawel Andruszkiewicz, Przemyslaw Rokita, Tomasz Trzcinski:
Comixify: Transform video into a comics. CoRR abs/1812.03473 (2018) - 2017
- [i9]Marek Kowalski, Jacek Naruniec, Tomasz Trzcinski:
Deep Alignment Network: A convolutional neural network for robust face alignment. CoRR abs/1706.01789 (2017) - [i8]Wojciech Stokowiec, Tomasz Trzcinski, Krzysztof Wolk, Krzysztof Marasek, Przemyslaw Rokita:
Shallow reading with Deep Learning: Predicting popularity of online content using only its title. CoRR abs/1707.06806 (2017) - [i7]Tomasz Trzcinski, Pawel Andruszkiewicz, Tomasz Bochenski, Przemyslaw Rokita:
Recurrent Neural Networks for Online Video Popularity Prediction. CoRR abs/1707.06807 (2017) - [i6]Jacek Komorowski, Tomasz Trzcinski:
Evaluation of Hashing Methods Performance on Binary Feature Descriptors. CoRR abs/1707.06825 (2017) - [i5]Ivona Tautkute, Aleksandra Mozejko, Wojciech Stokowiec, Tomasz Trzcinski, Lukasz Brocki, Krzysztof Marasek:
What Looks Good with my Sofa: Multimodal Search Engine for Interior Design. CoRR abs/1707.06907 (2017) - [i4]Maciej Suchecki, Tomasz Trzcinski:
Understanding Aesthetics in Photography using Deep Convolutional Neural Networks. CoRR abs/1707.08985 (2017) - [i3]Pawel Cyrta, Tomasz Trzcinski, Wojciech Stokowiec:
Speaker Diarization using Deep Recurrent Convolutional Neural Networks for Speaker Embeddings. CoRR abs/1708.02840 (2017) - [i2]Michal Komorowski, Tomasz Trzcinski:
Random Binary Trees for Approximate Nearest Neighbour Search in Binary Space. CoRR abs/1708.02976 (2017) - 2015
- [i1]Tomasz Trzcinski, Przemyslaw Rokita:
Predicting popularity of online videos using Support Vector Regression. CoRR abs/1510.06223 (2015)
Coauthor Index
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