123. Semantic Line Combination Detector

• Jinwon Ko, Dongkwon Jin, Chang-Su Kim (Korea University)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

122. Flow-Assisted Motion Learning Network for Weakly-Supervised Group Activity Recognition

• Muhammad Adi Nugroho, Sangmin Woo, Sumin Lee, Jinyoung Park, Yooseung Wang, Donguk Kim, Changick Kim (KAIST)
• European Conference on Computer Vision (ECCV), 2024

121. Spatio-Temporal Proximity-Aware Dual-Path Model for Panoramic Activity Recognition

• Sumin Lee, Yooseung Wang, Sangmin Woo, Changick Kim (KAIST)
• European Conference on Computer Vision (ECCV), 2024

120. MoAI: Mixture of All Intelligence for Large Language and Vision Models

• Byung-Kwan Lee, Beomchan Park, Chae Won Kim, Yong Man Ro (KAIST)
• European Conference on Computer Vision (ECCV), 2024

119. CoLLaVO: Crayon Large Language and Vision mOdel

• Byung-Kwan Lee, Beomchan Park, Chae Won Kim, Yong Man Ro (KAIST)
• Association for Computational Linguistics  (ACL), 2024

118. Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback

• Daechul Ahn, Yura Choi, Youngjae Yu, Dongyeop Kang, Jonghyun Choi (Seoul National University)
• Association for Computational Linguistics  (ACL), 2024

117. Online Continual Learning for Interactive Instruction Following Agents

• Byeonghwi Kim, Minhyuk Seo, Jonghyun Choi (Seoul National University)
• IEEE International Conference on Learning Representations  (ICLR), 2024

116. Diffusion-based Episodes Augmentation for Offline Multi-Agent Reinforcement Learning

• Jihwan Oh, Sungnyun Kim, Gahee Kim, Sunghwan Kim, Se-Young Yun (KAIST)
• IEEE International Conference on Machine Learning Workshop  (ICML), 2024

115. DPM: Dual Preferences based Multi Agent Reinforcement Learning

• Sehyeok Kang, Yongsik Lee, Se-Young Yun (KAIST)
• IEEE International Conference on Machine Learning Workshop  (ICML), 2024

114. Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning

• Jihwan Oh, Joonkee Kim, Minchan Jeong, Se-Young Yun (KAIST)
• International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2024

113. Retrieval-Augmented Natural Language Reasoning for Explainable Visual Question Answering

• Su Hyeon Lim, Minkuk Kim, Hyeon Bae Kim, Seong Tae Kim (Kyunghee University)
• IEEE International Conference on Image Processing Workshop  (ICIP), 2024

112. FedAvP: Augment Local Data via Shared Policy in Federated Learning

• Minui Hong · Junhyeog Yun · Insu Jeon · Gunhee Kim (Seoul National University)
• Conference on Neural Information Processing Systems (NeurIPS), 2024

111. DeFT-AN RT: Realtime Multichannel Speech Enhancement using Dense Frequency-Time Attentive Network and Non-overlapping Synthesis Window

• Dongheon Lee, Jung-Woo Choi (KAIST)
• Interspeech, 2024

110. Beyond Single Path Integrated Gradients for Reliable Input Attribution via Randomized Path Sampling

• Giyoung Jeon, Haedong Jeong, Jaesik Choi (KAIST)
• IEEE International Conference on Computer Vision (ICCV), 2024

109. Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations

• Hyeonjeong Ha, Minseon Kim, Sung Ju Hwang (KAIST)
• Conference on Neural Information Processing Systems (Neurips), 2024

108. Implicit 3D Human Mesh Recovery using Consistency with Pose and Shape from

• Hanbyel Cho, Yooshin Cho, Jaesung Ahn, Junmo Kim (KAIST)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

107. Data Poisoning Attack Aiming the Vulnerability of Continual Learning

• Gyojin Han, Jaehyun Choi, Hyeong Gwon Hong, Junmo Kim (KAIST)
• IEEE International Conference on Image Processing (ICIP), 2024

106. Multi-scale Diffusion Denoised Smoothing 

• Jongheon Jeong and Jinwoo Shin (KAIST)
• Conference on Neural Information Processing Systems (Neurips), 2024

105. Development of a Lunar Rover Simulator with an Interface for Reinforcement Learning

• Assawayut Khunmaturod, Dong Eui Chang (KAIST)
• International Conference on Automation, Control and Robotics Engineering (CACRE), 2024

104. DeFTMamba: Multichannel Universal Sound Separation and Polyphonic Audio Classification

• Dongheon Lee, Jeonwoo Choi (KAIST)
• IEEE International Conference on Acoustics, Speech, and Signal Processing  (ICASSP), 2024

103. DeFTAN-AA: Array Geometry Agnostic Multichannel Speech Enhancement

• Dongheon Lee, Jeonwoo Choi (KAIST)
• Interspeech, 2024

102. Adversarial Robustification via Text-to-Image Diffusion Models

• Daewon Choi, Jinwoo Shin (KAIST)
• European Conference on Computer Vision (ECCV), 2024

101. Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning

• Jihwan Oh, Joonkee Kim, Minchan Jeong, Se-Young Yun (KAIST)
•  International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2024

100. Wavelet-Guided Acceleration of Text Inversion in Diffusion-based Image Editing

•  Gwanhyeong Koo, Sunjae Yoon, Chang Dong Yoo (KAIST)
• IEEE International Conference on Acoustics, Speech, and Signal Processing  (ICASSP), 2024

99. Foreseeing Reconstruction Quality of Gradient Inversion: An Optimization Perspective

•  HyeongGwon Hong, Yooshin Cho, Hanbyel Cho, Jaesung Ahn, Junmo Kim (KAIST)
• AAAI Conference on Artificial Intelligence (AAAI), 2024

98. DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models

•  Sohyun An, Hayeon Lee, Jaehyeong Jo, Seanie Lee, Sung Ju Hwang (KAIST)
• International Conference on Learning Representations (ICLR), 2024

97. Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian Detection

• Taeheon Kim, Sebin Shin, Youngjoon Yu, Hak Gu Kim, Yong Man Ro (KAIST)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

96. FocoTrack: Multi Object Tracking by Focusing On Overlap in Low Frame Rate

•  Jaehyeok Lee, Jaehyun Park, Dongeui Chang (KAIST)
• IEEE International Conference on Robotics and Automation  (ICRA), 2024

95. Particle filter with stable embedding for state estimation of rigid body attitude system on S^3

• Huideok Jang, Jaehyun Park, Dongeui Chang (KAIST)
• IEEE International Conference on Robotics and Automation  (ICRA), 2024

94. Enhancing Audio-Visual Question Answering with Missing Modality via Trans-Modal Associative Learning

• Kyu Ri Park, Youngmin Oh, and Jung Uk Kim (KHU)
• IEEE International Conference on Acoustics, Speech, and Signal Processing  (ICASSP), 2024

93. Learning to Localize Sound Sources from Mixtures without Prior Source Knowledge

• Dongjin Kim, Sung Jin Um, Sangmin Lee, and Jung Uk Kim (KHU)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

92. WWW: A Unified Framework for Explaining What, Where and Why of Neural Networks by Interpretation of Neuron Concept

• Yong Hyun Ahn, Hyeon Bae Kim, Seong Tae Kim (KHU)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

91.  Do You Remember? Dense Video Captioning with Cross-Modal Memory Retrieval

• Minkuk Kim, Hyeon Bae Kim, Jinyoung Moon, Jinwoo Choi and Seong Tae Kim (KHU)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

90.  Learning Equi-angular Representations for Online Continual Learning

• Minhyuk Seo, Hyunseo Koh, Wonje Jeung, Min Jae Lee, San Kim, Hankook Lee, Sungjun Cho, Sungik Choi, Hyunwoo Kim, Jonghyun Choi (SNU)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

89. Federated Learning via Meta-Variational Dropout

• Insu Jeon, Minui Hong, Junhyeog Yun, Gunhee Kim (Seoul National University)
• Conference on Neural Information Processing Systems (Neurips), 2023

88. NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks

• Seokil Ham, Jungwuk Park, Dong-Jun Han, Jaekyun Moon (KAIST)
• Conference on Neural Information Processing Systems (Neurips), 2023

87. Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization

• Jungwuk Park, Dong-Jun Han, Soyeong Kim, Jaekyun Moon (KAIST)
•  International Conference on Machine Learning (ICML), 2023

86. LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework

• Woojun Kim, Jeonghye Kim, Youngchul Sung (KAIST)
•  International Conference on Machine Learning (ICML), 2023

85. Active learning for object detection with evidential deep learning and hierarchical uncertainty aggregation

• Younghyun Park, Wonjeong Choi, Soyeong Kim, Dong-Jun Han, Jaekyun Moon (KAIST)
• International Conference on Learning Representations (ICLR), 2023

84. Recursive Video Lane Detection

• Dongkwon Jin, Dahyun Kim, Chang-Su Kim (Korea University)
• IEEE International Conference on Computer Vision (ICCV), 2023

83. BiFormer: Learning Bilateral Motion Estimation via Bilateral Transformer for 4K Video Frame Interpolation

• Junheum Park, Jintae Kim, Chang-Su Kim (Korea University)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023

82. Audio-Visual Glance Network for Efficient Video Recognition

• Muhammad Adi Nugroho, Sangmin Woo, Sumin Lee, Changick Kim (KAIST)
• IEEE International Conference on Computer Vision (ICCV), 2023

81. Modality Mixer for Multi-modal Action Recognition

• Sumin Lee, Sangmin Woo, Yeonju Park, Muhammad Adi Nugroho, Changick Kim (KAIST)
• IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023

80. Towards Good Practices for Missing Modality Robust Action Recognition

• Sangmin Woo, Sumin Lee, Yeonju Park, Muhammad Adi Nugroho, and Changick Kim (KAIST)
• AAAI Conference on Artificial Intelligence (AAAI), 2023

79. Multispectral Invisible Coating: Laminated Visible-Thermal Physical Attack against Multispectral Object Detectors using Transparent Low-e films

• Taeheon Kim,  Youngjoon Yu, and Yong Man Ro (KAIST)
• AAAI Conference on Artificial Intelligence (AAAI), 2023

78. Similarity Relation Preserving Cross-Modal Learning For Multispectral Pedestrian Detection

• Jung Uk Kim; Yong Man Ro (KAIST)
• IEEE International Conference on Acoustics, Speech, and Signal Processing  (ICASSP), 2023

77. Mitigating Adversarial Vulnerability through Causal Parameter Estimation by Adversarial Double Machine Learning

• Byung-Kwan Lee, Junho Kim, Yong Man Ro (KAIST)
• IEEE International Conference on Computer Vision (ICCV), 2023

76. Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network by Adversarial Instrumental Variable

• Junho Kim, Byung-Kwan Lee, Yong Man Ro (KAIST)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023

75. DeFT-AN RT: Realtime Multichannel Speech Enhancement using Dense Frequency-Time Attentive Network and Non-overlapping Synthesis Window

• Dongheon Lee, Jung-Woo Choi (KAIST)
• Interspeech, 2023

74. Beyond Single Path Integrated Gradients for Reliable Input Attribution via Randomized Path Sampling

• Giyoung Jeon, Haedong Jeong, Jaesik Choi (KAIST)
• IEEE International Conference on Computer Vision (ICCV), 2023

73. Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations

• Hyeonjeong Ha, Minseon Kim, Sung Ju Hwang (KAIST)
• Conference on Neural Information Processing Systems (Neurips), 2023

72. Implicit 3D Human Mesh Recovery using Consistency with Pose and Shape from

• Hanbyel Cho, Yooshin Cho, Jaesung Ahn, Junmo Kim (KAIST)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023

71. Data Poisoning Attack Aiming the Vulnerability of Continual Learning

• Gyojin Han, Jaehyun Choi, Hyeong Gwon Hong, Junmo Kim (KAIST)
• IEEE International Conference on Image Processing (ICIP), 2023

70. Multi-scale Diffusion Denoised Smoothing 

• Jongheon Jeong and Jinwoo Shin (KAIST)
• Conference on Neural Information Processing Systems (Neurips), 2023

69. Enhancing Multiple Reliability Measures via Nuisance-extended Information Bottleneck

• Jongheon Jeong, Sihyun Yu, Hankook Lee, Jinwoo Shin (KAIST)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023

68. Confidence-aware Training of Smoothed Classifiers for Certified Robustness

• Jongheon Jeong, Seojin Kim, Jinwoo Shin (KAIST)
• AAAI Conference on Artificial Intelligence (AAAI), 2023

66. Future Transformer for Long-term Action Anticipation

• Dayoung Gong, Joonseok Lee, Manjin Kim, Seong Jong Ha, and Minsu Cho (POSTECH)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022

65. Integrative Few-shot Learning for Classification and Segmentation

• Dahyun Kang, and Minsu Cho (POSTECH)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022

64. UDA-COPE: Unsupervised Domain Adaptation for Category-Level Object Pose Estimation

• Taeyeop Lee, Byeong-Uk Lee, Inkyu Shin, Jaesung Choe, Ukcheol Shin, In So Kweon, and Kuk-Jin Yoon (KAIST)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022

63. Masking Adversarial Damage: Finding Adversarial Saliency for Robust and Sparse Networks

• Byung-Kwan Lee, Junho Kim, and Yong Man Ro (KAIST)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022

62. Moving Window Regression: A Novel Approach to Ordinal Regression

• Nyeong-Ho Shin, Seon-Ho Lee, and Chang-Su Kim (Korea University)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022

61. Distilled Gradient Aggregation: Purify Features for Input Attribution in the Deep Neural Networks

• Giyoung Jeon, Haedong Jeong, and Jaesik Choi (KAIST)
• Conference on Neural Information Processing Systems (Neurips), 2022

60. Geometric Order Learning for Rank Estimation

• Seon-Ho Lee, Nyeong Ho Shin, and Chang-Su Kim (Korea University)
• Conference on Neural Information Processing Systems (Neurips), 2022

59. MASER: Multi-Agent Reinforcement Learning with Subgoals Generated from Experience Replay Buffer

• Jeewon Jeon, Woojun Kim, Whiyoung Jung, and Youngchul Sung (KAIST)
• International Conference on Machine Learning (ICML), 2022

58. Online Hyperparameter Meta-Learning with Hypergradient Distillation

• Hae Beom Lee, Hayeon Lee, Jaewoong Shin, Eunho Yang, and Sung Ju Hwang (KAIST)
• International Conference on Learning Representations (ICLR), 2022

57. Neural Variational Dropout Processes

• Insu Jeon, Youngjin Park, and Gunhee Kim (Seoul National University)
• International Conference on Learning Representations (ICLR), 2022

56. Neural Processes with Stochastic Attention: Paying more attention to the context dataset

• Mingyu Kim, Kyeongryeol Go, and Se-Young Yun (KAIST)
• International Conference on Learning Representations (ICLR), 2022

55. Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs

• Fanchen Bu and Dong Eui Chang (KAIST)
• AAAI Conference on Artificial Intelligence (AAAI), 2022

54. Towards Versatile Pedestrian Detector with Multisensory-Matching and Multispectral Recalling Memory

• Jung Uk Kim, Sungjune Park, and Yong Man Ro (KAIST)
• AAAI Conference on Artificial Intelligence (AAAI), 2022

53. From Scratch to Sketch: Deep Decoupled Hierarchical Reinforcement Learning for Robotic Sketching Agent

• Ganghun Lee, Minji Kim, Minsu Lee, and Byoung-Tak Zhang (Seoul National University)
• IEEE International Conference on Robotics and Automation (ICRA), 2022

52. MAP: Multispectral Adversarial Patch to Attack Person Detection

• Taeheon Kim, Hong Joo Lee, and Yong Man Ro (KAIST)
• IEEE International Conference on Acoustics, Speech, and Signal Processing  (ICASSP), 2022

51. DRL-ISP: Multi-Objective Camera ISP with Deep Reinforcement Learning

• Ukcheol Shin, Kyunghyun Lee, and In So Kweon (KAIST)
• IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022

50. Model-free Unsupervised Anomaly Detection of a General Robotic System Using a Stacked LSTM and Its Application to a Fixed-wing Unmanned Aerial Vehicle

• Jaehyun Park and Dong Eui Chang (KAIST)
• IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022

49. Defending Physical Adversarial Attack on Object Detection via Adversarial Patch-Feature Energy

• Taeheon Kim, Youngjoon Yu, and Yong Man Ro (KAIST)
• ACM Multimedia (ACMMM), 2022

48. Cyclic Test Time Augmentation with Entropy Weight Method

• Sewhan Chun, Jae Young Lee, and Junmo Kim (KAIST)
• Conference on Uncertainty in Artificial Intelligence (UAI), 2022

47. Rethinking Efficacy of Softmax for Lightweight Non-local Neural Networks

• Yooshin Cho, Youngsoo Kim, Hanbyel Cho, Jaesung Ahn, Hyeong Gwon Hong,  and Junmo Kim (KAIST)
• IEEE International Conference on Image Processing (ICIP), 2022

46. Multi-contextual Predictions with Vision Transformer for Video Anomaly Detection

• Joo-Yeon Lee, Woo-Jeoung Nam, and Seong-Whan Lee (Korea University)
• International Conference on Pattern Recognition (ICPR), 2022

45. Multi-modal Characteristic Guided Depth Completion Network

• Yongjin Lee, Seokjun Park, Beomgu Kang, and Hyun Wook Park (KAIST)
• Asian Conference on Computer Vision (ACCV), 2022

44. A Study of Adaptive Process Mechanism based on Context-Awareness Embedded Middleware

• Dohyun Kim (Jeju University)
• International Conference on Multimedia Information Technology and Applications (MITA), 2022

43. Nonlinear Rescaling of Acquisition Metric Values Based on Distribution Fitting

• Jongeui Park and Youngchul Sung (KAIST)
• International Conference on Machine Learning Workshops (ICML Workshop), 2022

42. The StarCraft Multi-Agent Challenges+ : Learning of Sub-tasks and Environmental Benefits without Precise Reward Functions

• Mingyu Kim, Jihwan Oh, Yongsik Lee, Joonkee Kim, SeongHwan Kim, Song Chong, and Se-Young Yun (KAIST)
• International Conference on Machine Learning Workshops (ICML Workshop), 2022

41. Risk Perspective Exploration in Distributional Reinforcement Learning

• Jihwan Oh, Joonkee Kim, and Se-Young Yun (KAIST)
• International Conference on Machine Learning Workshops (ICML Workshop), 2022

40. ALASCA: Rethinking Label Smoothing for Deep Learning Under Label Noise

• Jongwoo Ko, Bongsoo Yi, and Se-Young Yun (KAIST)
• International Conference on Machine Learning Workshops (ICML Workshop), 2022

39. Active Object Detection with Epistemic Uncertainty and Hierarchical Information Aggregation

• Younghyun Park, Soyeong Kim, Wonjeong Choi, Dong-Jun Han, and Jaekyun Moon (KAIST)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshop), 2022

38. Perturbed Quantile Regression for Distributional Reinforcement Learning

• Taehyun Cho, Seungyub Han, Heesoo Lee, Kyungjae Lee, and Jungwoo Lee (Seoul National University)
• Conference on Neural Information Processing Systems (Neurips Workshop), 2022

37. Sample-efficient Adversarial Imitation Learning

• Dahuin Jung, Hyungyu Lee, and Sungroh Yoon (Seoul National University)
• Conference on Neural Information Processing Systems (Neurips Workshop), 2022

36. Adaptive Methods for Nonconvex Continual Learning

• Seungyub Han, Yeongmo Kim, Tae Hyun Cho, and Jungwoo Lee (Seoul National University)
• Conference on Neural Information Processing Systems (Neurips Workshop), 2022

35. Rainbow Memory: Continual Learning with a Memory of Diverse Samples

• Jihwan Bang, Heesu Kim, YoungJoon Yoo, Jung-Woo Ha, and Jonghyun Choi (GIST)
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021

34. SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness

• Jongheon Jeong, Sejun Park, Minkyu Kim, Heung-Chang Lee, Doguk Kim, and Jinwoo Shin (KAIST)
• Conference on Neural Information Processing Systems (Neurips), 2021

33. HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning

• Hayeon Lee, Sewoong Lee, Song Chong, and Sung Ju Hwang (KAIST)
• Conference on Neural Information Processing Systems (Neurips), 2021

32. Distilling Robust and Non-Robust Features in Adversarial Examples by Information Bottleneck

• Junho Kim, Byung-Kwan Lee, and Yong Man Ro (KAIST)
• Conference on Neural Information Processing Systems (Neurips), 2021

31. A Max-Min Entropy Framework for Reinforcement Learning

• Seungyul Han and Youngchul Sung (UNIST, KAIST)
• Conference on Neural Information Processing Systems (Neurips), 2021

30. CAG-QIL: Context-Aware Actionness Grouping via Q Imitation Learning for Online Temporal Action Localization

• Hyolim Kang, Kyungmin Kim, Yumin Ko, and Seon Joo Kim (Yonsei University)
• IEEE International Conference on Computer Vision (ICCV), 2021

29. Robust Small-scale Pedestrian Detection with Cued Recall via Memory Learning

• Jung Uk Kim, Sungjune Park, and Yong Man Ro (KAIST)
• IEEE International Conference on Computer Vision (ICCV), 2021

28. Weakly Supervised Segmentation of Small Building with Point Labels

• Jae-Hun Lee, ChanYoung Kim, and Sanghoon Sull (Korea University)
• IEEE International Conference on Computer Vision (ICCV), 2021

27. Zero-shot Natural Language Video Localization

• Jinwoo Nam, Daechul Ahn, Dongyeop Kang, Seong Jong Ha, and Jonghyun Choi (GIST)
• IEEE International Conference on Computer Vision (ICCV), 2021

26. Rethinking Deep Image Prior for Denoising

• Yeonsik Jo, Se Young Chun, and Jonghyun Choi (Seoul National University, GIST)
• IEEE International Conference on Computer Vision (ICCV), 2021

25. Federated Continual Learning with Weighted Inter-client Transfer

• Jaehong Yoon, Wonyong Jeong, Giwoong Lee, Eunho Yang, and Sung Ju Hwang (KAIST)
• International Conference on Machine Learning (ICML), 2021

24. Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets

• Hayeon Lee, Eunyoung Hyung, and Sung Ju Hwang (KAIST)
• International Conference on Learning Representations (ICLR), 2021

23. Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

• Wonyong Jeong, Jaehong Yoon, Eunho Yang, and Sung Ju Hwang (KAIST)
• International Conference on Learning Representations (ICLR), 2021

22. MASKER: Masked Keyword Regularization for Reliable Text Classification

• Seung Jun Moon, Sangwoo Mo, Kimin Lee, Jaeho Lee, and Jinwoo Shin (KAIST)
• AAAI Conference on Artificial Intelligence (AAAI), 2021

21. An Unsupervised Way to Understand Artifact Generating Internal Units in Generative Neural Networks

• Haedong Jeong, Jiyeon Han, and Jaesik Choi (UNIST, KAIST)
• AAAI Conference on Artificial Intelligence (AAAI), 2021

20. IB-GAN: Disentangled Representation Learning With Information Bottleneck Generative Adversarial Networks

• Insu Jeon, Wonkwang Lee, Myeongjang Pyeon, and Gunhee Kim (Seoul National University, KAIST)
• AAAI Conference on Artificial Intelligence (AAAI), 2021

19. Towards Robust Training of Multi-Sensor Data Fusion Network against Adversarial Examples in Semantic Segmentation

• Youngjoon Yu, Hong Joo Lee, Byeong Cheon Kim, Jung Uk Kim, and Yong Man Ro (KAIST)
• IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2021

18. Adversarially Robust Multi-sensor Fusion Model Training via Random Feature Fusion for Semantic Segmentation

• Hong Joo Lee and Yong Man Ro (KAIST)
• IEEE International Conference on Image Processing (ICIP), 2021

17. Robust Decision-based Black-box Adversarial Attack via Coarse-to-Fine Random Search

• Byeong Cheon Kim, Youngjoon Yu, and Yong Man Ro (KAIST)
• IEEE International Conference on Image Processing (ICIP), 2021

16. Toddler-Guidance Learning: Impacts of Critical Period on Multimodal AI Agents

• Junseok Park, Kwanyoung Park, Hyunseok Oh, Ganghun Lee, Minsu Lee, Youngki Lee, and Byoung-Tak Zhang (Seoul National University)
• ACM International Conference on Multimodal Interaction (ICMI), 2021

15. 4W1H Keyword Extraction based Summarization Model

• Seungyeon Lee, Taewon Park, and Minho Lee (Kyungpook National University)
• International Conference on Electronics, Information, and Communication (ICEIC), 2021

14. C3: Contrastive Learning for Cross-domain Correspondence in Few-shot Image Generation

• Hyuk-Gi Lee, Gi-Cheon Kang, Chang-Hoon Jeong, Han-Wool Sul, and Byoung-Tak Zhang (Seoul National University)
• Neural Information Processing Systems Workshop (Neurips Workshop), 2021

13. Neural Processes with Stochastic Attention: Paying more attention to the context dataset

• Mingyu Kim, Kyeongryeol Go, and Se-Young Yun (KAIST)
• Neural Information Processing Systems Workshop (Neurips Workshop), 2021

12. Consistency Regularization for Certified Robustness of Smoothed Classifiers

• Jongheon Jeong and Jinwoo Shin (KAIST)
• Conference on Neural Information Processing Systems (Neurips), 2020 

11. Cross-Identity Motion Transfer for Arbitrary Objects Through Pose-Attentive Video Reassembling

• Subin Jeon, Seonghyeon Nam, Seoung Wug Oh, and Seon Joo Kim (Yonsei University)
• European Conference on Computer Vision (ECCV), 2020 

10. Multi-Loss Rebalancing Algorithm for Monocular Depth Estimation

• Jae-Han Lee and Chang-Su Kim (Korea University)
• European Conference on Computer Vision (ECCV), 2020

9. Dual Attention in Time and Frequency Domain for Voice Activity Detection

• Joohyung Lee, Youngmoon Jung, and Hoirin Kim (KAIST)
• International Speech Communication Association (INTERSPEECH), 2020

8. Multi-Task Network for Noise-Robust Keyword Spotting and Speaker Verification using CTC-based Soft VAD and Global Query Attention

• Myunghun Jung, Youngmoon Jung, Jahyun Goo, and Hoirin Kim (KAIST)
• International Speech Communication Association (INTERSPEECH), 2020

7. Robust Ensemble Model Training via Random Layer Sampling Against Adversarial Attack

• Hakmin Lee, Hong Joo Lee, Seong Tae Kim, and Yong Man Ro (KAIST)
• British Machine Vision Conference (BMVC), 2020

6. Towards Human-like Interpretable Object Detection via Spatial Relation Encoding

• Jung Uk Kim, Sungjune Park, and Yong Man Ro (KAIST)
• IEEE International Conference on Image Processing (ICIP), 2020

5. Comprehensive Facial Expression Synthesis using Human-Interpretable Language

• Joanna Hong, Jung Uk Kim, Sangmin Lee, and Yong Man Ro (KAIST)
• IEEE International Conference on Image Processing (ICIP), 2020

4. Fake Video Detection with Certainty-based Attention Network

• Dae Hwi Choi, Hong Joo Lee, Sangmin Lee, Jung Uk Kim, and Yong Man Ro (KAIST)
• IEEE International Conference on Image Processing (ICIP), 2020

3. Revisiting Role of Autoencoder in Adversarial Settings

• Byeong Cheon Kim, Jung Uk Kim, Hakmin Lee, and Yong Man Ro (KAIST)
• IEEE International Conference on Image Processing (ICIP), 2020

2. Self-Training of Graph Neural Networks using Similarity Reference for Robust Training with Noisy Labels

• Hyoungseob Park, Minki Jeong, Youngeun Kim, and Changick Kim (KAIST)
• IEEE International Conference on Image Processing (ICIP), 2020

1. Dynamic Noise Embedding: Noise Aware Training and Adaptation for Speech Enhancement

• Joohyung Lee, Youngmoon Jung, Myunghun Jung, and Hoirin Kim (KAIST)
• Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2020