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ORCIDJoost van de Weijer 0001
Person information
- affiliation: Universitat Autònoma de Barcelona, Spain
Other persons with the same name
- Joost van de Weijer 0002
![[0000-0001-9843-3143]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-9843-3143")
— Lund University, Centre for Languages and Literature, Sweden
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2020 – today
- 2023
[j48]Shiqi Yang, Yaxing Wang, Luis Herranz, Shangling Jui, Joost van de Weijer:
Casting a BAIT for offline and online source-free domain adaptation. Comput. Vis. Image Underst. 234: 103747 (2023)- [j47]Marc Masana, Xialei Liu, Bartlomiej Twardowski, Mikel Menta, Andrew D. Bagdanov, Joost van de Weijer:
Class-Incremental Learning: Survey and Performance Evaluation on Image Classification. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5513-5533 (2023) - [c113]Chenshen Wu, Joost van de Weijer:
Density Map Distillation for Incremental Object Counting. CVPR Workshops 2023: 2506-2515 - [c112]Jia-Wen Xiao, Chang-Bin Zhang, Jiekang Feng, Xialei Liu, Joost van de Weijer, Ming-Ming Cheng:
Endpoints Weight Fusion for Class Incremental Semantic Segmentation. CVPR 2023: 7204-7213 - [c111]Senmao Li, Joost van de Weijer, Yaxing Wang, Fahad Shahbaz Khan, Meiqin Liu, Jian Yang:
3D-Aware Multi-Class Image-to-Image Translation with NeRFs. CVPR 2023: 12652-12662 - [c110]Simone Zini, Alex Gomez-Villa, Marco Buzzelli, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer:
Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training. ICLR 2023 - [c109]Dipam Goswami, René Schuster, Joost van de Weijer, Didier Stricker:
Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic Segmentation. WACV 2023: 3194-3203 - [i100]Mert Kilickaya, Joost van de Weijer, Yuki M. Asano:
Towards Label-Efficient Incremental Learning: A Survey. CoRR abs/2302.00353 (2023) - [i99]Dawid Rymarczyk, Joost van de Weijer, Bartosz Zielinski, Bartlomiej Twardowski:
ICICLE: Interpretable Class Incremental Continual Learning. CoRR abs/2303.07811 (2023) - [i98]Senmao Li, Joost van de Weijer, Yaxing Wang, Fahad Shahbaz Khan, Meiqin Liu, Jian Yang:
3D-Aware Multi-Class Image-to-Image Translation with NeRFs. CoRR abs/2303.15012 (2023) - [i97]Senmao Li, Joost van de Weijer, Taihang Hu, Fahad Shahbaz Khan, Qibin Hou, Yaxing Wang, Jian Yang:
StyleDiffusion: Prompt-Embedding Inversion for Text-Based Editing. CoRR abs/2303.15649 (2023) - [i96]Antonio Carta, Andrea Cossu, Vincenzo Lomonaco, Davide Bacciu, Joost van de Weijer:
Projected Latent Distillation for Data-Agnostic Consolidation in Distributed Continual Learning. CoRR abs/2303.15888 (2023) - [i95]Chenshen Wu, Joost van de Weijer:
Density Map Distillation for Incremental Object Counting. CoRR abs/2304.05255 (2023) - [i94]Albin Soutif-Cormerais, Antonio Carta, Joost van de Weijer:
Improving Online Continual Learning Performance and Stability with Temporal Ensembles. CoRR abs/2306.16817 (2023) - [i93]Yuyang Liu, Yang Cong, Dipam Goswami, Xialei Liu, Joost van de Weijer:
Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection. CoRR abs/2307.12427 (2023) - [i92]Albin Soutif-Cormerais, Antonio Carta, Andrea Cossu, Julio Hurtado, Vincenzo Lomonaco, Joost van de Weijer, Hamed Hemati:
A Comprehensive Empirical Evaluation on Online Continual Learning. CoRR abs/2308.10328 (2023) - [i91]Fei Yang, Kai Wang, Joost van de Weijer:
ScrollNet: Dynamic Weight Importance for Continual Learning. CoRR abs/2308.16567 (2023) - [i90]Shiqi Yang, Yaxing Wang, Joost van de Weijer, Luis Herranz, Shangling Jui, Jian Yang:
Trust your Good Friends: Source-free Domain Adaptation by Reciprocal Neighborhood Clustering. CoRR abs/2309.00528 (2023) - [i89]Eduardo Aguilar, Bogdan Raducanu, Petia Radeva, Joost van de Weijer:
Continual Evidential Deep Learning for Out-of-Distribution Detection. CoRR abs/2309.02995 (2023) - [i88]Alex Gomez-Villa, Bartlomiej Twardowski, Kai Wang, Joost van de Weijer:
Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning. CoRR abs/2309.06086 (2023) - 2022
- [c108]Kai Wang, Chenshen Wu, Andy Bagdanov, Xialei Liu, Shiqi Yang, Shangling Jui, Joost van de Weijer:
Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification. BMVC 2022: 38 - [c107]Kai Wang, Fei Yang, Joost van de Weijer:
Attention Distillation: self-supervised vision transformer students need more guidance. BMVC 2022: 666 - [c106]Bojana Gajic, Ariel Amato, Ramon Baldrich, Joost van de Weijer, Carlo Gatta:
Area Under the ROC Curve Maximization for Metric Learning. CVPR Workshops 2022: 2806-2815 - [c105]Kai Wang, Xialei Liu, Andy Bagdanov, Luis Herranz, Shangling Jui, Joost van de Weijer:
Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition. CVPR Workshops 2022: 3728-3738 - [c104]Francesco Pelosin, Saurav Jha, Andrea Torsello, Bogdan Raducanu, Joost van de Weijer:
Towards Exemplar-Free Continual Learning in Vision Transformers: an Account of Attention, Functional and Weight Regularization. CVPR Workshops 2022: 3819-3828 - [c103]Héctor Laria Mantecon, Yaxing Wang, Joost van de Weijer, Bogdan Raducanu:
Transferring Unconditional to Conditional GANs with Hyper-Modulation. CVPR Workshops 2022: 3839-3848 - [c102]Alex Gomez-Villa, Bartlomiej Twardowski, Lu Yu, Andrew D. Bagdanov, Joost van de Weijer:
Continually Learning Self-Supervised Representations with Projected Functional Regularization. CVPR Workshops 2022: 3866-3876 - [c101]Aitor Alvarez-Gila, Joost van de Weijer, Yaxing Wang, Estíbaliz Garrote:
MVMO: A Multi-Object Dataset for Wide Baseline Multi-View Semantic Segmentation. ICIP 2022: 1166-1170 - [c100]Yaxing Wang, Joost van de Weijer, Lu Yu, Shangling Jui:
Distilling GANs with Style-Mixed Triplets for X2I Translation with Limited Data. ICLR 2022 - [c99]Vacit Oguz Yazici, Joost van de Weijer, Longlong Yu:
Visual Transformers with Primal Object Queries for Multi-Label Image Classification. ICPR 2022: 3014-3020 - [c98]Shiqi Yang, Yaxing Wang, Kai Wang, Shangling Jui, Joost van de Weijer:
Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation. NeurIPS 2022 - [c97]Javad Zolfaghari Bengar, Joost van de Weijer, Laura Lopez-Fuentes, Bogdan Raducanu:
Class-Balanced Active Learning for Image Classification. WACV 2022: 3707-3716 - [i87]Vacit Oguz Yazici, Longlong Yu, Arnau Ramisa, Luis Herranz, Joost van de Weijer:
Main Product Detection with Graph Networks for Fashion. CoRR abs/2201.10431 (2022) - [i86]Simone Zini, Marco Buzzelli, Bartlomiej Twardowski, Joost van de Weijer:
Planckian jitter: enhancing the color quality of self-supervised visual representations. CoRR abs/2202.07993 (2022) - [i85]Francesco Pelosin, Saurav Jha, Andrea Torsello, Bogdan Raducanu, Joost van de Weijer:
Towards Exemplar-Free Continual Learning in Vision Transformers: an Account of Attention, Functional and Weight Regularization. CoRR abs/2203.13167 (2022) - [i84]Shiqi Yang, Yaxing Wang, Kai Wang, Shangling Jui, Joost van de Weijer:
Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation. CoRR abs/2205.04183 (2022) - [i83]Aitor Alvarez-Gila, Joost van de Weijer, Yaxing Wang, Estíbaliz Garrote:
MVMO: A Multi-Object Dataset for Wide Baseline Multi-View Semantic Segmentation. CoRR abs/2205.15452 (2022) - [i82]Shiqi Yang, Yaxing Wang, Kai Wang, Shangling Jui, Joost van de Weijer:
One Ring to Bring Them All: Towards Open-Set Recognition under Domain Shift. CoRR abs/2206.03600 (2022) - [i81]Kai Wang, Fei Yang, Joost van de Weijer:
Attention Distillation: self-supervised vision transformer students need more guidance. CoRR abs/2210.00944 (2022) - [i80]Kai Wang, Chenshen Wu, Andy Bagdanov, Xialei Liu, Shiqi Yang, Shangling Jui, Joost van de Weijer:
Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification. CoRR abs/2210.01600 (2022) - [i79]Dipam Goswami, René Schuster, Joost van de Weijer, Didier Stricker:
Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic Segmentation. CoRR abs/2210.07207 (2022) - [i78]Marco Cotogni, Fei Yang, Claudio Cusano, Andrew D. Bagdanov, Joost van de Weijer:
Gated Class-Attention with Cascaded Feature Drift Compensation for Exemplar-free Continual Learning of Vision Transformers. CoRR abs/2211.12292 (2022) - 2021
- [j46]Yaxing Wang, Abel Gonzalez-Garcia, Luis Herranz, Joost van de Weijer:
Controlling biases and diversity in diverse image-to-image translation. Comput. Vis. Image Underst. 202: 103082 (2021) - [j45]Carola Figueroa Flores, David Berga, Joost van de Weijer, Bogdan Raducanu:
Saliency for free: Saliency prediction as a side-effect of object recognition. Pattern Recognit. Lett. 150: 1-7 (2021) - [j44]Kai Wang, Joost van de Weijer, Luis Herranz:
ACAE-REMIND for online continual learning with compressed feature replay. Pattern Recognit. Lett. 150: 122-129 (2021) - [j43]Shiqi Yang, Kai Wang, Luis Herranz, Joost van de Weijer:
On Implicit Attribute Localization for Generalized Zero-Shot Learning. IEEE Signal Process. Lett. 28: 872-876 (2021) - [j42]Sudeep Katakol, Basem Elbarashy, Luis Herranz, Joost van de Weijer, Antonio M. López:
Distributed Learning and Inference With Compressed Images. IEEE Trans. Image Process. 30: 3069-3083 (2021) - [c96]Kai Wang, Xialei Liu, Luis Herranz, Joost van de Weijer:
HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification. BMVC 2021: 119 - [c95]Javad Zolfaghari Bengar, Bogdan Raducanu, Joost van de Weijer:
When Deep Learners Change Their Mind: Learning Dynamics for Active Learning. CAIP (1) 2021: 403-413 - [c94]Marc Masana, Tinne Tuytelaars, Joost van de Weijer:
Ternary Feature Masks: Zero-Forgetting for Task-Incremental Learning. CVPR Workshops 2021: 3570-3579 - [c93]Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L. Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido M. van de Ven, Martin Mundt, Qi She, Keiland W. Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German Ignacio Parisi, Fabio Cuzzolin, Andreas S. Tolias, Simone Scardapane, Luca Antiga, Subutai Ahmad, Adrian Popescu, Christopher Kanan, Joost van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni:
Avalanche: An End-to-End Library for Continual Learning. CVPR Workshops 2021: 3600-3610 - [c92]Kai Wang, Luis Herranz, Joost van de Weijer:
Continual Learning in Cross-Modal Retrieval. CVPR Workshops 2021: 3628-3638 - [c91]Shiqi Yang, Yaxing Wang, Joost van de Weijer, Luis Herranz, Shangling Jui:
Generalized Source-free Domain Adaptation. ICCV 2021: 8958-8967 - [c90]Yaxing Wang, Héctor Laria Mantecon, Joost van de Weijer, Laura Lopez-Fuentes, Bogdan Raducanu:
TransferI2I: Transfer Learning for Image-to-Image Translation from Small Datasets. ICCV 2021: 13990-13999 - [c89]Javad Zolfaghari Bengar, Joost van de Weijer, Bartlomiej Twardowski, Bogdan Raducanu:
Reducing Label Effort: Self-Supervised meets Active Learning. ICCVW 2021: 1631-1639 - [c88]Shiqi Yang, Yaxing Wang, Joost van de Weijer, Luis Herranz, Shangling Jui:
Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation. NeurIPS 2021: 29393-29405 - [c87]Carola Figueroa Flores, Bogdan Raducanu, David Berga, Joost van de Weijer:
Hallucinating Saliency Maps for Fine-grained Image Classification for Limited Data Domains. VISIGRAPP (4: VISAPP) 2021: 163-171 - [i77]Akshita Gupta, Sanath Narayan, Salman H. Khan, Fahad Shahbaz Khan, Ling Shao, Joost van de Weijer:
Generative Multi-Label Zero-Shot Learning. CoRR abs/2101.11606 (2021) - [i76]Shiqi Yang, Kai Wang, Luis Herranz, Joost van de Weijer:
On Implicit Attribute Localization for Generalized Zero-Shot Learning. CoRR abs/2103.04704 (2021) - [i75]Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Antonio Carta, Gabriele Graffieti, Tyler L. Hayes, Matthias De Lange, Marc Masana, Jary Pomponi, Gido M. van de Ven, Martin Mundt, Qi She, Keiland W. Cooper, Jeremy Forest, Eden Belouadah, Simone Calderara, German Ignacio Parisi, Fabio Cuzzolin, Andreas S. Tolias, Simone Scardapane, Luca Antiga, Subutai Amhad, Adrian Popescu, Christopher Kanan, Joost van de Weijer, Tinne Tuytelaars, Davide Bacciu, Davide Maltoni:
Avalanche: an End-to-End Library for Continual Learning. CoRR abs/2104.00405 (2021) - [i74]Kai Wang, Luis Herranz, Joost van de Weijer:
Continual learning in cross-modal retrieval. CoRR abs/2104.06806 (2021) - [i73]Yaxing Wang, Abel Gonzalez-Garcia, Chenshen Wu, Luis Herranz, Fahad Shahbaz Khan, Shangling Jui, Joost van de Weijer:
MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains. CoRR abs/2104.13742 (2021) - [i72]Yaxing Wang, Héctor Laria Mantecon, Joost van de Weijer, Laura Lopez-Fuentes, Bogdan Raducanu:
TransferI2I: Transfer Learning for Image-to-Image Translation from Small Datasets. CoRR abs/2105.06219 (2021) - [i71]Kai Wang, Luis Herranz, Joost van de Weijer:
ACAE-REMIND for Online Continual Learning with Compressed Feature Replay. CoRR abs/2105.08595 (2021) - [i70]Albin Soutif-Cormerais, Marc Masana, Joost van de Weijer, Bartlomiej Twardowski:
On the importance of cross-task features for class-incremental learning. CoRR abs/2106.11930 (2021) - [i69]Carola Figueroa Flores, David Berga, Joost van de Weijer, Bogdan Raducanu:
Saliency for free: Saliency prediction as a side-effect of object recognition. CoRR abs/2107.09628 (2021) - [i68]Javad Zolfaghari Bengar, Bogdan Raducanu, Joost van de Weijer:
When Deep Learners Change Their Mind: Learning Dynamics for Active Learning. CoRR abs/2107.14707 (2021) - [i67]Shiqi Yang, Yaxing Wang, Joost van de Weijer, Luis Herranz, Shangling Jui:
Generalized Source-free Domain Adaptation. CoRR abs/2108.01614 (2021) - [i66]Javad Zolfaghari Bengar, Joost van de Weijer, Bartlomiej Twardowski, Bogdan Raducanu:
Reducing Label Effort: Self-Supervised meets Active Learning. CoRR abs/2108.11458 (2021) - [i65]Shiqi Yang, Yaxing Wang, Joost van de Weijer, Luis Herranz, Shangling Jui:
Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation. CoRR abs/2110.04202 (2021) - [i64]Javad Zolfaghari Bengar, Joost van de Weijer, Laura Lopez-Fuentes, Bogdan Raducanu:
Class-Balanced Active Learning for Image Classification. CoRR abs/2110.04543 (2021) - [i63]Kai Wang, Xialei Liu, Luis Herranz, Joost van de Weijer:
HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification. CoRR abs/2110.11148 (2021) - [i62]Kai Wang, Xialei Liu, Andrew D. Bagdanov, Luis Herranz, Shangling Jui, Joost van de Weijer:
Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition. CoRR abs/2111.04993 (2021) - [i61]Héctor Laria Mantecon, Yaxing Wang, Joost van de Weijer, Bogdan Raducanu:
Hyper-GAN: Transferring Unconditional to Conditional GANs with HyperNetworks. CoRR abs/2112.02219 (2021) - [i60]Vacit Oguz Yazici, Joost van de Weijer, Longlong Yu:
Visual Transformers with Primal Object Queries for Multi-Label Image Classification. CoRR abs/2112.05485 (2021) - [i59]Alex Gomez-Villa, Bartlomiej Twardowski, Lu Yu, Andrew D. Bagdanov, Joost van de Weijer:
Continually Learning Self-Supervised Representations with Projected Functional Regularization. CoRR abs/2112.15022 (2021) - 2020
- [j41]Fei Yang, Yongmei Cheng, Joost van de Weijer, Mikhail G. Mozerov:
Improved Discrete Optical Flow Estimation With Triple Image Matching Cost. IEEE Access 8: 17093-17102 (2020) - [j40]Yaxing Wang, Luis Herranz, Joost van de Weijer:
Mix and Match Networks: Cross-Modal Alignment for Zero-Pair Image-to-Image Translation. Int. J. Comput. Vis. 128(12): 2849-2872 (2020) - [j39]Rahma Kalboussi, Aymen Azaza, Joost van de Weijer, Mehrez Abdellaoui, Ali Douik:
Object proposals for salient object segmentation in videos. Multim. Tools Appl. 79(13-14): 8677-8693 (2020) - [j38]Gabriel Villalonga, Joost van de Weijer, Antonio M. López:
Recognizing New Classes with Synthetic Data in the Loop: Application to Traffic Sign Recognition. Sensors 20(3): 583 (2020) - [j37]Aymen Azaza, Joost van de Weijer, Ali Douik, Javad Zolfaghari Bengar, Marc Masana:
Saliency from High-Level Semantic Image Features. SN Comput. Sci. 1(4): 200 (2020) - [j36]Fei Yang, Luis Herranz, Joost van de Weijer, José Antonio Iglesias Guitián, Antonio M. López, Mikhail G. Mozerov:
Variable Rate Deep Image Compression With Modulated Autoencoder. IEEE Signal Process. Lett. 27: 331-335 (2020) - [c86]Xialei Liu, Chenshen Wu, Mikel Menta, Luis Herranz, Bogdan Raducanu, Andrew D. Bagdanov, Shangling Jui, Joost van de Weijer:
Generative Feature Replay For Class-Incremental Learning. CVPR Workshops 2020: 915-924 - [c85]Yaxing Wang, Salman H. Khan, Abel Gonzalez-Garcia, Joost van de Weijer, Fahad Shahbaz Khan:
Semi-Supervised Learning for Few-Shot Image-to-Image Translation. CVPR 2020: 4452-4461 - [c84]Lu Yu, Bartlomiej Twardowski, Xialei Liu, Luis Herranz, Kai Wang, Yongmei Cheng, Shangling Jui, Joost van de Weijer:
Semantic Drift Compensation for Class-Incremental Learning. CVPR 2020: 6980-6989 - [c83]Yaxing Wang, Abel Gonzalez-Garcia, David Berga, Luis Herranz, Fahad Shahbaz Khan, Joost van de Weijer:
MineGAN: Effective Knowledge Transfer From GANs to Target Domains With Few Images. CVPR 2020: 9329-9338 - [c82]Vacit Oguz Yazici, Abel Gonzalez-Garcia, Arnau Ramisa, Bartlomiej Twardowski, Joost van de Weijer:
Orderless Recurrent Models for Multi-Label Classification. CVPR 2020: 13437-13446 - [c81]Minghan Li, Xialei Liu, Joost van de Weijer, Bogdan Raducanu:
Learning to Rank for Active Learning: A Listwise Approach. ICPR 2020: 5587-5594 - [c80]Riccardo Del Chiaro, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer:
RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning. NeurIPS 2020 - [c79]Yaxing Wang, Lu Yu, Joost van de Weijer:
DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs. NeurIPS 2020 - [i58]Mikel Menta, Adriana Romero, Joost van de Weijer:
Learning to adapt class-specific features across domains for semantic segmentation. CoRR abs/2001.08311 (2020) - [i57]Marc Masana, Tinne Tuytelaars, Joost van de Weijer:
Ternary Feature Masks: continual learning without any forgetting. CoRR abs/2001.08714 (2020) - [i56]Yaxing Wang, Salman H. Khan, Abel Gonzalez-Garcia, Joost van de Weijer, Fahad Shahbaz Khan:
Semi-supervised Learning for Few-shot Image-to-Image Translation. CoRR abs/2003.13853 (2020) - [i55]Lu Yu, Bartlomiej Twardowski, Xialei Liu, Luis Herranz, Kai Wang, Yongmei Cheng, Shangling Jui, Joost van de Weijer:
Semantic Drift Compensation for Class-Incremental Learning. CoRR abs/2004.00440 (2020) - [i54]Xialei Liu, Chenshen Wu, Mikel Menta, Luis Herranz, Bogdan Raducanu, Andrew D. Bagdanov, Shangling Jui, Joost van de Weijer:
Generative Feature Replay For Class-Incremental Learning. CoRR abs/2004.09199 (2020) - [i53]Sudeep Katakol, Basem Elbarashy, Luis Herranz, Joost van de Weijer, Antonio M. López:
Distributed Learning and Inference with Compressed Images. CoRR abs/2004.10497 (2020) - [i52]Shiqi Yang, Kai Wang, Luis Herranz, Joost van de Weijer:
Simple and effective localized attribute representations for zero-shot learning. CoRR abs/2006.05938 (2020) - [i51]Kai Wang, Luis Herranz, Anjan Dutta, Joost van de Weijer:
Bookworm continual learning: beyond zero-shot learning and continual learning. CoRR abs/2006.15176 (2020) - [i50]Marc Masana, Bartlomiej Twardowski, Joost van de Weijer:
On Class Orderings for Incremental Learning. CoRR abs/2007.02145 (2020) - [i49]Riccardo Del Chiaro, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer:
RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning. CoRR abs/2007.06271 (2020) - [i48]David Berga, Marc Masana, Joost van de Weijer:
Disentanglement of Color and Shape Representations for Continual Learning. CoRR abs/2007.06356 (2020) - [i47]Carola Figueroa Flores, Bogdan Raducanu, David Berga, Joost van de Weijer:
Hallucinating Saliency Maps for Fine-Grained Image Classification for Limited Data Domains. CoRR abs/2007.12562 (2020) - [i46]Minghan Li, Xialei Liu, Joost van de Weijer, Bogdan Raducanu:
Learning to Rank for Active Learning: A Listwise Approach. CoRR abs/2008.00078 (2020) - [i45]Shiqi Yang, Yaxing Wang, Joost van de Weijer, Luis Herranz, Shangling Jui:
Unsupervised Domain Adaptation without Source Data by Casting a BAIT. CoRR abs/2010.12427 (2020) - [i44]Marc Masana, Xialei Liu, Bartlomiej Twardowski, Mikel Menta, Andrew D. Bagdanov, Joost van de Weijer:
Class-incremental learning: survey and performance evaluation. CoRR abs/2010.15277 (2020) - [i43]Yaxing Wang, Lu Yu, Joost van de Weijer:
DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs. CoRR abs/2011.05867 (2020) - [i42]Lu Yu, Xialei Liu, Joost van de Weijer:
Self-Training for Class-Incremental Semantic Segmentation. CoRR abs/2012.03362 (2020)
2010 – 2019
- 2019
- [j35]Aitor Alvarez-Gila, Adrian Galdran, Estíbaliz Garrote, Joost van de Weijer:
Self-supervised blur detection from synthetically blurred scenes. Image Vis. Comput. 92 (2019) - [j34]Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov:
Exploiting Unlabeled Data in CNNs by Self-Supervised Learning to Rank. IEEE Trans. Pattern Anal. Mach. Intell. 41(8): 1862-1878 (2019) - [j33]Carola Figueroa Flores, Abel Gonzalez-Garcia, Joost van de Weijer, Bogdan Raducanu:
Saliency for fine-grained object recognition in domains with scarce training data. Pattern Recognit. 94: 62-73 (2019) - [j32]Mikhail G. Mozerov, Fei Yang, Joost van de Weijer:
Sparse Data Interpolation Using the Geodesic Distance Affinity Space. IEEE Signal Process. Lett. 26(6): 943-947 (2019) - [j31]Lichao Zhang, Abel Gonzalez-Garcia, Joost van de Weijer, Martin Danelljan, Fahad Shahbaz Khan:
Synthetic Data Generation for End-to-End Thermal Infrared Tracking. IEEE Trans. Image Process. 28(4): 1837-1850 (2019) - [j30]Mikhail G. Mozerov, Joost van de Weijer:
One-View Occlusion Detection for Stereo Matching With a Fully Connected CRF Model. IEEE Trans. Image Process. 28(6): 2936-2947 (2019) - [c78]Lu Yu, Vacit Oguz Yazici, Xialei Liu, Joost van de Weijer, Yongmei Cheng, Arnau Ramisa:
Learning Metrics From Teachers: Compact Networks for Image Embedding. CVPR 2019: 2907-2916 - [c77]