Orderless Tracking through Model-Averaged Posterior Estimation. - Seunghoon Hong; Suha Kwak; Bohyung Han (ICCV, 2013)

Joint Segmentation and Pose Tracking of Human in Natural Videos. - Taegyu Lim; Seunghoon Hong; Bohyung Han; Joon Hee Han (ICCV, 2013)

Visual Tracking by Sampling Tree-Structured Graphical Models. - Seunghoon Hong; Bohyung Han (ECCV (1), 2014)

The Visual Object Tracking VOT2014 Challenge Results. - 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; et al. (ECCV Workshops (2), 2014)

Online Graph-Based Tracking. - Hyeonseob Nam; Seunghoon Hong; Bohyung Han (ECCV (5), 2014)

Learning Deconvolution Network for Semantic Segmentation. - Hyeonwoo Noh; Seunghoon Hong; Bohyung Han (ICCV, 2015)

Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network. - Seunghoon Hong; Tackgeun You; Suha Kwak; Bohyung Han (ICML, 2015)

Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation. - Seunghoon Hong; Hyeonwoo Noh; Bohyung Han (NIPS, 2015)

Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network. - Seunghoon Hong; Junhyuk Oh; Honglak Lee; Bohyung Han (CVPR, 2016)

Joint Image Clustering and Labeling by Matrix Factorization. - Seunghoon Hong; Jonghyun Choi; Jan Feyereisl; Bohyung Han; Larry S. Davis (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Weakly Supervised Semantic Segmentation Using Superpixel Pooling Network. - Suha Kwak; Seunghoon Hong; Bohyung Han (AAAI, 2017)

Weakly Supervised Semantic Segmentation Using Web-Crawled Videos. - Seunghoon Hong; Donghun Yeo; Suha Kwak; Honglak Lee; Bohyung Han (CVPR, 2017)

Decomposing Motion and Content for Natural Video Sequence Prediction. - Ruben Villegas; Jimei Yang; Seunghoon Hong; Xunyu Lin; Honglak Lee (ICLR (Poster), 2017)

Personalized Image Aesthetic Quality Assessment by Joint Regression and Ranking. - Kayoung Park; Seunghoon Hong; Mooyeol Baek; Bohyung Han (WACV, 2017)

Weakly Supervised Learning with Deep Convolutional Neural Networks for Semantic Segmentation: Understanding Semantic Layout of Images with Minimum Human Supervision. - Seunghoon Hong; Suha Kwak; Bohyung Han (IEEE Signal Process. Mag., 2017)

Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis. - Seunghoon Hong; Dingdong Yang; Jongwook Choi; Honglak Lee (CVPR, 2018)

Learning Hierarchical Semantic Image Manipulation through Structured Representations. - Seunghoon Hong; Xinchen Yan; Thomas E. Huang; Honglak Lee (NeurIPS, 2018)

A Study on the Physiological and Psychological Stress Relief Effects of Vertical Gardens on Human Body: 3 Different Construction Methods of Vertical Gardens. - Kwang-Pyo Hong; Hyukjae Lee; Seunghoon Hong (CISP-BMEI, 2019)

Adversarial Defense via Learning to Generate Diverse Attacks. - Yunseok Jang 001; Tianchen Zhao; Seunghoon Hong; Honglak Lee (ICCV, 2019)

Diversity-Sensitive Conditional Generative Adversarial Networks. - Dingdong Yang; Seunghoon Hong; Yunseok Jang 001; Tianchen Zhao; Honglak Lee (ICLR (Poster), 2019)

Interpretable Text-to-Image Synthesis with Hierarchical Semantic Layout Generation. - Seunghoon Hong; Dingdong Yang; Jongwook Choi; Honglak Lee (Explainable AI, 2019)

Residual Neural Processes. - Byung-Jun Lee 001; Seunghoon Hong; Kee-Eung Kim (AAAI, 2020)

High-Fidelity Synthesis with Disentangled Representation. - Wonkwang Lee; Donggyun Kim; Seunghoon Hong; Honglak Lee (ECCV (26), 2020)

Variational Interaction Information Maximization for Cross-domain Disentanglement. - HyeongJoo Hwang; Geon-Hyeong Kim; Seunghoon Hong; Kee-Eung Kim (NeurIPS, 2020)

Learning to Generate Novel Classes for Deep Metric Learning. - Kyungmoon Lee; Sungyeon Kim; Seunghoon Hong; Suha Kwak (BMVC, 2021)

SetVAE: Learning Hierarchical Composition for Generative Modeling of Set-Structured Data. - Jinwoo Kim; Jaehoon Yoo; Juho Lee 001; Seunghoon Hong (CVPR, 2021)

Improving Unsupervised Image Clustering With Robust Learning. - Sungwon Park 001; Sungwon Han 001; Sundong Kim; Danu Kim; Sungkyu Park; Seunghoon Hong; Meeyoung Cha (CVPR, 2021)

Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction. - Wonkwang Lee; Whie Jung; Han Zhang 010; Ting Chen 001; Jing Yu Koh; Thomas E. Huang; Hyungsuk Yoon; Honglak Lee; Seunghoon Hong (ICLR, 2021)

Multi-View Representation Learning via Total Correlation Objective. - HyeongJoo Hwang; Geon-Hyeong Kim; Seunghoon Hong; Kee-Eung Kim (NeurIPS, 2021)

Transformers Generalize DeepSets and Can be Extended to Graphs & Hypergraphs. - Jinwoo Kim; Saeyoon Oh; Seunghoon Hong (NeurIPS, 2021)

Neural Contrast Enhancement of CT Image. - Minkyo Seo; Dongkeun Kim; Kyungmoon Lee; Seunghoon Hong; Jae Seok Bae; Jung Hoon Kim; Suha Kwak (WACV, 2021)

Transformers Generalize DeepSets and Can be Extended to Graphs and Hypergraphs. - Jinwoo Kim; Saeyoon Oh; Seunghoon Hong (CoRR, 2021)

Learning Economic Indicators by Aggregating Multi-Level Geospatial Information. - Sungwon Park 001; Sungwon Han 001; Donghyun Ahn; Jaeyeon Kim; Jeasurk Yang; Susang Lee; Seunghoon Hong; Jihee Kim; Sangyoon Park; Hyunjoo Yang; Meeyoung Cha (AAAI, 2022)

Part-based Pseudo Label Refinement for Unsupervised Person Re-identification. - Yoonki Cho; Woo Jae Kim; Seunghoon Hong; Sung-Eui Yoon (CVPR, 2022)

Equivariant Hypergraph Neural Networks. - Jinwoo Kim; Saeyoon Oh; Sungjun Cho; Seunghoon Hong (ECCV (21), 2022)

Learning Continuous Representation of Audio for Arbitrary Scale Super Resolution. - Jaechang Kim 001; Yunjoo Lee; Seunghoon Hong; Jungseul Ok (ICASSP, 2022)

Diverse Generative Perturbations on Attention Space for Transferable Adversarial Attacks. - Woo Jae Kim; Seunghoon Hong; Sung-Eui Yoon (ICIP, 2022)

Multi-Task Processes. - Donggyun Kim; Seongwoong Cho; Wonkwang Lee; Seunghoon Hong (ICLR, 2022)

Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost. - Sungjun Cho; Seonwoo Min; Jinwoo Kim; Moontae Lee; Honglak Lee; Seunghoon Hong (NeurIPS, 2022)

Pure Transformers are Powerful Graph Learners. - Jinwoo Kim; Dat Nguyen; Seonwoo Min; Sungjun Cho; Moontae Lee; Honglak Lee; Seunghoon Hong (NeurIPS, 2022)

Pure Transformers are Powerful Graph Learners. - Jinwoo Kim; Tien Dat Nguyen; Seonwoo Min; Sungjun Cho; Moontae Lee; Honglak Lee; Seunghoon Hong (CoRR, 2022)

Diverse Generative Adversarial Perturbations on Attention Space for Transferable Adversarial Attacks. - Woo Jae Kim; Seunghoon Hong; Sung-Eui Yoon (CoRR, 2022)

Towards End-to-End Generative Modeling of Long Videos with Memory-Efficient Bidirectional Transformers. - Jaehoon Yoo; Semin Kim; Doyup Lee; Chiheon Kim; Seunghoon Hong (CVPR, 2023)

Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching. - Donggyun Kim; Jinwoo Kim; Seongwoong Cho; Chong Luo; Seunghoon Hong (ICLR, 2023)

Information-Theoretic State Space Model for Multi-View Reinforcement Learning. - HyeongJoo Hwang; Seokin Seo; Youngsoo Jang; Sungyoon Kim; Geon-Hyeong Kim; Seunghoon Hong; Kee-Eung Kim (ICML, 2023)

Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance. - Jinwoo Kim; Dat Nguyen; Ayhan Suleymanzade; Hyeokjun An; Seunghoon Hong (NeurIPS, 2023)

Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance. - Jinwoo Kim; Tien Dat Nguyen; Ayhan Suleymanzade; Hyeokjun An; Seunghoon Hong (CoRR, 2023)

Learning Symmetrization for Equivariance with Orbit Distance Minimization. - Tien Dat Nguyen; Jinwoo Kim; Hongseok Yang; Seunghoon Hong (CoRR, 2023)

Chameleon: A Data-Efficient Generalist for Dense Visual Prediction in the Wild. - Donggyun Kim; Seongwoong Cho; Semin Kim; Chong Luo; Seunghoon Hong (ECCV (23), 2024)

MetaWeather: Few-Shot Weather-Degraded Image Restoration. - Youngrae Kim; Younggeol Cho; Thanh-Tung Nguyen; Seunghoon Hong; Dongman Lee (ECCV (73), 2024)

Learning to Compose: Improving Object Centric Learning by Injecting Compositionality. - Whie Jung; Jaehoon Yoo; Sungjin Ahn; Seunghoon Hong (ICLR, 2024)

Meta-Controller: Few-Shot Imitation of Unseen Embodiments and Tasks in Continuous Control. - Seongwoong Cho; Donggyun Kim; Jinwoo Lee; Seunghoon Hong (NeurIPS, 2024)

Simulation-Free Training of Neural ODEs on Paired Data. - Semin Kim; Jaehoon Yoo; Jinwoo Kim; Yeonwoo Cha; Saehoon Kim; Seunghoon Hong (NeurIPS, 2024)

Learning to Merge Tokens via Decoupled Embedding for Efficient Vision Transformers. - Dong Hoon Lee; Seunghoon Hong (NeurIPS, 2024)

Revisiting Weight Averaging for Model Merging. - Jiho Choi; Donggyun Kim; Chanhyuk Lee; Seunghoon Hong (CoRR, 2024)

3D Denoisers Are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation. - Sungjun Cho; Dae-Woong Jeong; Sung Moon Ko; Jinwoo Kim; Sehui Han; Seunghoon Hong; Honglak Lee; Moontae Lee (AAAI, 2025)

Revisiting Random Walks for Learning on Graphs. - Jinwoo Kim; Olga Zaghen; Ayhan Suleymanzade; Youngmin Ryou; Seunghoon Hong (ICLR, 2025)

Feature Augmentation Based Test-Time Adaptation. - Younggeol Cho; Youngrae Kim; Junho Yoon; Seunghoon Hong; Dongman Lee (WACV, 2025)

AdaRank: Adaptive Rank Pruning for Enhanced Model Merging. - Chanhyuk Lee; Jiho Choi; Chanryeol Lee; Donggyun Kim; Seunghoon Hong (CoRR, 2025)

HyperFlow: Gradient-Free Emulation of Few-Shot Fine-Tuning. - Donggyun Kim; Chanwoo Kim; Seunghoon Hong (CoRR, 2025)

Reward-Agnostic Prompt Optimization for Text-to-Image Diffusion Models. - Semin Kim; Yeonwoo Cha; Jaehoon Yoo; Seunghoon Hong (CoRR, 2025)

ReDi: Rectified Discrete Flow. - Jaehoon Yoo; Wonjung Kim; Seunghoon Hong (CoRR, 2025)