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Journal Articles
- 2017
[j2]Seunghoon Hong, Suha Kwak
, Bohyung Han:
Weakly Supervised Learning with Deep Convolutional Neural Networks for Semantic Segmentation: Understanding Semantic Layout of Images with Minimum Human Supervision. IEEE Signal Process. Mag. 34(6): 39-49 (2017)- 2016
- [j1]Seunghoon Hong, Jonghyun Choi, Jan Feyereisl, Bohyung Han, Larry S. Davis:
Joint Image Clustering and Labeling by Matrix Factorization. IEEE Trans. Pattern Anal. Mach. Intell. 38(7): 1411-1424 (2016)
Conference and Workshop Papers
- 2024
- [c41]Whie Jung, Jaehoon Yoo, Sungjin Ahn, Seunghoon Hong:
Learning to Compose: Improving Object Centric Learning by Injecting Compositionality. ICLR 2024 - 2023
- [c40]Jaehoon Yoo, Semin Kim, Doyup Lee, Chiheon Kim, Seunghoon Hong:
Towards End-to-End Generative Modeling of Long Videos with Memory-Efficient Bidirectional Transformers. CVPR 2023: 22888-22897 - [c39]Donggyun Kim, Jinwoo Kim, Seongwoong Cho, Chong Luo, Seunghoon Hong:
Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching. ICLR 2023 - [c38]HyeongJoo Hwang, Seokin Seo, Youngsoo Jang, Sungyoon Kim, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim:
Information-Theoretic State Space Model for Multi-View Reinforcement Learning. ICML 2023: 14249-14282 - [c37]Jinwoo Kim, Dat Nguyen, Ayhan Suleymanzade, Hyeokjun An, Seunghoon Hong:
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance. NeurIPS 2023 - 2022
- [c36]Sungwon Park, Sungwon Han, Donghyun Ahn, Jaeyeon Kim, Jeasurk Yang, Susang Lee, Seunghoon Hong, Jihee Kim, Sangyoon Park, Hyunjoo Yang, Meeyoung Cha:
Learning Economic Indicators by Aggregating Multi-Level Geospatial Information. AAAI 2022: 12053-12061 - [c35]Yoonki Cho, Woo Jae Kim, Seunghoon Hong, Sung-Eui Yoon:
Part-based Pseudo Label Refinement for Unsupervised Person Re-identification. CVPR 2022: 7298-7308 - [c34]Jinwoo Kim, Saeyoon Oh, Sungjun Cho, Seunghoon Hong:
Equivariant Hypergraph Neural Networks. ECCV (21) 2022: 86-103 - [c33]Jaechang Kim, Yunjoo Lee, Seunghoon Hong, Jungseul Ok:
Learning Continuous Representation of Audio for Arbitrary Scale Super Resolution. ICASSP 2022: 3703-3707 - [c32]Woo Jae Kim, Seunghoon Hong, Sung-Eui Yoon:
Diverse Generative Perturbations on Attention Space for Transferable Adversarial Attacks. ICIP 2022: 281-285 - [c31]Donggyun Kim, Seongwoong Cho, Wonkwang Lee, Seunghoon Hong:
Multi-Task Processes. ICLR 2022 - [c30]Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong:
Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost. NeurIPS 2022 - [c29]Jinwoo Kim, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong:
Pure Transformers are Powerful Graph Learners. NeurIPS 2022 - 2021
- [c28]Kyungmoon Lee, Sungyeon Kim, Seunghoon Hong, Suha Kwak:
Learning to Generate Novel Classes for Deep Metric Learning. BMVC 2021: 166 - [c27]Sungwon Park, Sungwon Han, Sundong Kim, Danu Kim, Sungkyu Park, Seunghoon Hong, Meeyoung Cha:
Improving Unsupervised Image Clustering With Robust Learning. CVPR 2021: 12278-12287 - [c26]Jinwoo Kim, Jaehoon Yoo, Juho Lee, Seunghoon Hong:
SetVAE: Learning Hierarchical Composition for Generative Modeling of Set-Structured Data. CVPR 2021: 15059-15068 - [c25]Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas E. Huang, Hyungsuk Yoon, Honglak Lee, Seunghoon Hong:
Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction. ICLR 2021 - [c24]HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim:
Multi-View Representation Learning via Total Correlation Objective. NeurIPS 2021: 12194-12207 - [c23]Jinwoo Kim, Saeyoon Oh, Seunghoon Hong:
Transformers Generalize DeepSets and Can be Extended to Graphs & Hypergraphs. NeurIPS 2021: 28016-28028 - [c22]Minkyo Seo, Dongkeun Kim, Kyungmoon Lee, Seunghoon Hong, Jae Seok Bae, Jung Hoon Kim, Suha Kwak:
Neural Contrast Enhancement of CT Image. WACV 2021: 3972-3981 - 2020
- [c21]Byung-Jun Lee, Seunghoon Hong, Kee-Eung Kim:
Residual Neural Processes. AAAI 2020: 4545-4552 - [c20]Wonkwang Lee, Donggyun Kim, Seunghoon Hong, Honglak Lee:
High-Fidelity Synthesis with Disentangled Representation. ECCV (26) 2020: 157-174 - [c19]HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim:
Variational Interaction Information Maximization for Cross-domain Disentanglement. NeurIPS 2020 - 2019
- [c18]Kwang-Pyo Hong, Hyukjae Lee, Seunghoon Hong:
A Study on the Physiological and Psychological Stress Relief Effects of Vertical Gardens on Human Body: 3 Different Construction Methods of Vertical Gardens. CISP-BMEI 2019: 1-8 - [c17]Yunseok Jang, Tianchen Zhao, Seunghoon Hong, Honglak Lee:
Adversarial Defense via Learning to Generate Diverse Attacks. ICCV 2019: 2740-2749 - [c16]Dingdong Yang, Seunghoon Hong, Yunseok Jang, Tianchen Zhao, Honglak Lee:
Diversity-Sensitive Conditional Generative Adversarial Networks. ICLR (Poster) 2019 - 2018
- [c15]Seunghoon Hong, Dingdong Yang, Jongwook Choi, Honglak Lee:
Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis. CVPR 2018: 7986-7994 - [c14]Seunghoon Hong, Xinchen Yan, Thomas E. Huang, Honglak Lee:
Learning Hierarchical Semantic Image Manipulation through Structured Representations. NeurIPS 2018: 2713-2723 - 2017
- [c13]Suha Kwak, Seunghoon Hong, Bohyung Han:
Weakly Supervised Semantic Segmentation Using Superpixel Pooling Network. AAAI 2017: 4111-4117 - [c12]Seunghoon Hong, Donghun Yeo, Suha Kwak, Honglak Lee, Bohyung Han:
Weakly Supervised Semantic Segmentation Using Web-Crawled Videos. CVPR 2017: 2224-2232 - [c11]Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, Honglak Lee:
Decomposing Motion and Content for Natural Video Sequence Prediction. ICLR (Poster) 2017 - [c10]Kayoung Park, Seunghoon Hong, Mooyeol Baek, Bohyung Han:
Personalized Image Aesthetic Quality Assessment by Joint Regression and Ranking. WACV 2017: 1206-1214 - 2016
- [c9]Seunghoon Hong, Junhyuk Oh, Honglak Lee, Bohyung Han:
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network. CVPR 2016: 3204-3212 - 2015
- [c8]Hyeonwoo Noh, Seunghoon Hong, Bohyung Han:
Learning Deconvolution Network for Semantic Segmentation. ICCV 2015: 1520-1528 - [c7]Seunghoon Hong, Tackgeun You, Suha Kwak, Bohyung Han:
Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network. ICML 2015: 597-606 - [c6]Seunghoon Hong, Hyeonwoo Noh, Bohyung Han:
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation. NIPS 2015: 1495-1503 - 2014
- [c5]Seunghoon Hong, Bohyung Han:
Visual Tracking by Sampling Tree-Structured Graphical Models. ECCV (1) 2014: 1-16 - [c4]Hyeonseob Nam, Seunghoon Hong, Bohyung Han:
Online Graph-Based Tracking. ECCV (5) 2014: 112-126 - [c3]Matej Kristan, Roman P. Pflugfelder, Ales Leonardis, Jiri Matas, Luka Cehovin, Georg Nebehay, Tomás Vojír, Gustavo Fernández, Alan Lukezic, Aleksandar Dimitriev, Alfredo Petrosino, Amir Saffari, Bo Li, Bohyung Han, Cherkeng Heng, Christophe Garcia, Dominik Pangersic, Gustav Häger, Fahad Shahbaz Khan, Franci Oven, Horst Possegger, Horst Bischof, Hyeonseob Nam, Jianke Zhu, Jijia Li, Jin Young Choi, Jinwoo Choi, João F. Henriques, Joost van de Weijer, Jorge Batista, Karel Lebeda, Kristoffer Öfjäll, Kwang Moo Yi, Lei Qin, Longyin Wen, Mario Edoardo Maresca, Martin Danelljan, Michael Felsberg, Ming-Ming Cheng, Philip H. S. Torr, Qingming Huang, Richard Bowden, Sam Hare, Samantha YueYing Lim, Seunghoon Hong, Shengcai Liao, Simon Hadfield, Stan Z. Li, Stefan Duffner, Stuart Golodetz, Thomas Mauthner, Vibhav Vineet, Weiyao Lin, Yang Li, Yuankai Qi, Zhen Lei, Zhi Heng Niu:
The Visual Object Tracking VOT2014 Challenge Results. ECCV Workshops (2) 2014: 191-217 - 2013
- [c2]Taegyu Lim, Seunghoon Hong, Bohyung Han, Joon Hee Han:
Joint Segmentation and Pose Tracking of Human in Natural Videos. ICCV 2013: 833-840 - [c1]Seunghoon Hong, Suha Kwak, Bohyung Han:
Orderless Tracking through Model-Averaged Posterior Estimation. ICCV 2013: 2296-2303
Parts in Books or Collections
- 2019
- [p1]Seunghoon Hong, Dingdong Yang, Jongwook Choi, Honglak Lee:
Interpretable Text-to-Image Synthesis with Hierarchical Semantic Layout Generation. Explainable AI 2019: 77-95
Informal and Other Publications
- 2024
- [i32]Donggyun Kim, Seongwoong Cho, Semin Kim, Chong Luo, Seunghoon Hong:
Chameleon: A Data-Efficient Generalist for Dense Visual Prediction in the Wild. CoRR abs/2404.18459 (2024) - [i31]Whie Jung, Jaehoon Yoo, Sungjin Ahn, Seunghoon Hong:
Learning to Compose: Improving Object Centric Learning by Injecting Compositionality. CoRR abs/2405.00646 (2024) - [i30]Jinwoo Kim, Olga Zaghen, Ayhan Suleymanzade, Youngmin Ryou, Seunghoon Hong:
Revisiting Random Walks for Learning on Graphs. CoRR abs/2407.01214 (2024) - 2023
- [i29]Jaehoon Yoo, Semin Kim, Doyup Lee, Chiheon Kim, Seunghoon Hong:
Towards End-to-End Generative Modeling of Long Videos with Memory-Efficient Bidirectional Transformers. CoRR abs/2303.11251 (2023) - [i28]Donggyun Kim, Jinwoo Kim, Seongwoong Cho, Chong Luo, Seunghoon Hong:
Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching. CoRR abs/2303.14969 (2023) - [i27]Jinwoo Kim, Tien Dat Nguyen, Ayhan Suleymanzade, Hyeokjun An, Seunghoon Hong:
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance. CoRR abs/2306.02866 (2023) - [i26]Sungjun Cho, Dae-Woong Jeong, Sung Moon Ko, Jinwoo Kim, Sehui Han, Seunghoon Hong, Honglak Lee, Moontae Lee:
3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation. CoRR abs/2309.04062 (2023) - [i25]Tien Dat Nguyen, Jinwoo Kim, Hongseok Yang, Seunghoon Hong:
Learning Symmetrization for Equivariance with Orbit Distance Minimization. CoRR abs/2311.07143 (2023) - 2022
- [i24]Kyungmoon Lee, Sungyeon Kim, Seunghoon Hong, Suha Kwak:
Learning to Generate Novel Classes for Deep Metric Learning. CoRR abs/2201.01008 (2022) - [i23]Yoonki Cho, Woo Jae Kim, Seunghoon Hong, Sung-Eui Yoon:
Part-based Pseudo Label Refinement for Unsupervised Person Re-identification. CoRR abs/2203.14675 (2022) - [i22]Sungwon Park, Sungwon Han, Donghyun Ahn, Jaeyeon Kim, Jeasurk Yang, Susang Lee, Seunghoon Hong, Jihee Kim, Sangyoon Park, Hyunjoo Yang, Meeyoung Cha:
Learning Economic Indicators by Aggregating Multi-Level Geospatial Information. CoRR abs/2205.01472 (2022) - [i21]Jinwoo Kim, Tien Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong:
Pure Transformers are Powerful Graph Learners. CoRR abs/2207.02505 (2022) - [i20]Woo Jae Kim, Seunghoon Hong, Sung-Eui Yoon:
Diverse Generative Adversarial Perturbations on Attention Space for Transferable Adversarial Attacks. CoRR abs/2208.05650 (2022) - [i19]Jinwoo Kim, Saeyoon Oh, Sungjun Cho, Seunghoon Hong:
Equivariant Hypergraph Neural Networks. CoRR abs/2208.10428 (2022) - [i18]Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong:
Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost. CoRR abs/2210.15541 (2022) - 2021
- [i17]Jinwoo Kim, Jaehoon Yoo, Juho Lee, Seunghoon Hong:
SetVAE: Learning Hierarchical Composition for Generative Modeling of Set-Structured Data. CoRR abs/2103.15619 (2021) - [i16]Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas E. Huang, Hyungsuk Yoon, Honglak Lee, Seunghoon Hong:
Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction. CoRR abs/2104.06697 (2021) - [i15]Jinwoo Kim, Saeyoon Oh, Seunghoon Hong:
Transformers Generalize DeepSets and Can be Extended to Graphs and Hypergraphs. CoRR abs/2110.14416 (2021) - [i14]Donggyun Kim, Seongwoong Cho, Wonkwang Lee, Seunghoon Hong:
Multi-Task Processes. CoRR abs/2110.14953 (2021) - [i13]Jaechang Kim, Yunjoo Lee, Seunghoon Hong, Jungseul Ok:
Learning Continuous Representation of Audio for Arbitrary Scale Super Resolution. CoRR abs/2111.00195 (2021) - 2020
- [i12]Wonkwang Lee, Donggyun Kim, Seunghoon Hong, Honglak Lee:
High-Fidelity Synthesis with Disentangled Representation. CoRR abs/2001.04296 (2020) - [i11]HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim:
Variational Interaction Information Maximization for Cross-domain Disentanglement. CoRR abs/2012.04251 (2020) - [i10]Sungwon Park, Sungwon Han, Sundong Kim, Danu Kim, Sungkyu Park, Seunghoon Hong, Meeyoung Cha:
Improving Unsupervised Image Clustering With Robust Learning. CoRR abs/2012.11150 (2020) - 2019
- [i9]Dingdong Yang, Seunghoon Hong, Yunseok Jang, Tianchen Zhao, Honglak Lee:
Diversity-Sensitive Conditional Generative Adversarial Networks. CoRR abs/1901.09024 (2019) - 2018
- [i8]Seunghoon Hong, Dingdong Yang, Jongwook Choi, Honglak Lee:
Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis. CoRR abs/1801.05091 (2018) - [i7]Seunghoon Hong, Xinchen Yan, Thomas E. Huang, Honglak Lee:
Learning Hierarchical Semantic Image Manipulation through Structured Representations. CoRR abs/1808.07535 (2018) - 2017
- [i6]Seunghoon Hong, Donghun Yeo, Suha Kwak, Honglak Lee, Bohyung Han:
Weakly Supervised Semantic Segmentation using Web-Crawled Videos. CoRR abs/1701.00352 (2017) - [i5]Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, Honglak Lee:
Decomposing Motion and Content for Natural Video Sequence Prediction. CoRR abs/1706.08033 (2017) - 2015
- [i4]Seunghoon Hong, Tackgeun You, Suha Kwak, Bohyung Han:
Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network. CoRR abs/1502.06796 (2015) - [i3]Hyeonwoo Noh, Seunghoon Hong, Bohyung Han:
Learning Deconvolution Network for Semantic Segmentation. CoRR abs/1505.04366 (2015) - [i2]Seunghoon Hong, Hyeonwoo Noh, Bohyung Han:
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation. CoRR abs/1506.04924 (2015) - [i1]Seunghoon Hong, Junhyuk Oh, Bohyung Han, Honglak Lee:
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network. CoRR abs/1512.07928 (2015)
Coauthor Index
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