| 2026 | ACL | Open Your Model's Eyes: Video and Context-Aware Multimodal Backchannel Prediction. | Min-Jae Kim, Jun-Yeong Moon, Mujeen Sung, Gyeong-Moon Park |
| 2025 | AAAI | Multispectral Pedestrian Detection with Sparsely Annotated Label. | Chan Lee, Seungho Shin, Gyeong-Moon Park, Jung Uk Kim |
| 2025 | CVPR | Universal Domain Adaptation for Semantic Segmentation. | Seun-An Choe, Keon-Hee Park, Jinwoo Choi, Gyeong-Moon Park |
| 2025 | CVPR | PCBEAR: Pose Concept Bottleneck for Explainable Action Recognition. | Jongseo Lee, Wooil Lee, Gyeong-Moon Park, Seong Tae Kim, Jinwoo Choi |
| 2025 | CVPR | ESC: Erasing Space Concept for Knowledge Deletion. | Tae-Young Lee, Sundong Park, Minwoo Jeon, Hyoseok Hwang, Gyeong-Moon Park |
| 2025 | CVPR | Test-Time Fine-Tuning of Image Compression Models for Multi-Task Adaptability. | Unki Park, Seongmoon Jeong, Youngchan Jang, Gyeong-Moon Park, Jong Hwan Ko |
| 2025 | ICCV | ESSENTIAL: Episodic and Semantic Memory Integration for Video Class-Incremental Learning. | Jongseo Lee, Kyungho Bae, Kyle Min, Gyeong-Moon Park, Jinwoo Choi |
| 2025 | ICCV | GeoAvatar: Adaptive Geometrical Gaussian Splatting for 3D Head Avatar. | Seungjun Moon, Hah Min Lew, Seungeun Lee, Ji-Su Kang, Gyeong-Moon Park |
| 2025 | ICCV | SFUOD: Source-Free Unknown Object Detection. | Keon-Hee Park, Seun-An Choe, Gyeong-Moon Park |
| 2025 | ICML | Do Not Mimic My Voice : Speaker Identity Unlearning for Zero-Shot Text-to-Speech. | Taesoo Kim, Jinju Kim, Dongchan Kim, Jong Hwan Ko, Gyeong-Moon Park |
| 2025 | ICML | When Will It Fail?: Anomaly to Prompt for Forecasting Future Anomalies in Time Series. | Min-Yeong Park, Won-Jeong Lee, Seong Tae Kim, Gyeong-Moon Park |
| 2025 | WACV | WINE: Wavelet-Guided GAN Inversion and Editing for High-Fidelity Refinement. | Chaewon Kim, Seung Jun Moon, Gyeong-Moon Park |
| 2025 | WACV | Towards High-fidelity Head Blending with Chroma Keying for Industrial Applications. | Hah Min Lew, Sahng-Min Yoo, Hyunwoo Kang, Gyeong-Moon Park |
| 2024 | CVPR | Open-Set Domain Adaptation for Semantic Segmentation. | Seun-An Choe, Ah-Hyung Shin, Keon-Hee Park, Jinwoo Choi, Gyeong-Moon Park |
| 2024 | CVPR | Pre-trained Vision and Language Transformers are Few-Shot Incremental Learners. | Keon-Hee Park, Kyungwoo Song, Gyeong-Moon Park |
| 2024 | CVPR | Generative Unlearning for Any Identity. | Juwon Seo, Sung-Hoon Lee, Tae-Young Lee, Seungjun Moon, Gyeong-Moon Park |
| 2024 | ECCV | Towards Model-Agnostic Dataset Condensation by Heterogeneous Models. | Jun-Yeong Moon, Jung Uk Kim, Gyeong-Moon Park |
| 2024 | ECCV | Versatile Incremental Learning: Towards Class and Domain-Agnostic Incremental Learning. | Min-Yeong Park, Jae-Ho Lee, Gyeong-Moon Park |
| 2024 | ECCV | Online Continuous Generalized Category Discovery. | Keon-Hee Park, Hakyung Lee, Kyungwoo Song, Gyeong-Moon Park |
| 2024 | EMNLP | CED: Comparing Embedding Differences for Detecting Out-of-Distribution and Hallucinated Text. | Hakyung Lee, Keon-Hee Park, Hoyoon Byun, Jeyoon Yeom, Jihee Kim, Gyeong-Moon Park, Kyungwoo Song |
| 2024 | WACV | GLAD: Global-Local View Alignment and Background Debiasing for Unsupervised Video Domain Adaptation with Large Domain Gap. | Hyogun Lee, Kyungho Bae, Seong Jong Ha, Yumin Ko, Gyeong-Moon Park, Jinwoo Choi |
| 2024 | WACV | RADIO: Reference-Agnostic Dubbing Video Synthesis. | Dongyeun Lee, Chaewon Kim, Sangjoon Yu, Jaejun Yoo, Gyeong-Moon Park |
| 2023 | CVPR | LINe: Out-of-Distribution Detection by Leveraging Important Neurons. | Yong Hyun Ahn, Gyeong-Moon Park, Seong Tae Kim |
| 2023 | ICCV | Online Class Incremental Learning on Stochastic Blurry Task Boundary via Mask and Visual Prompt Tuning. | Jun-Yeong Moon, Keon-Hee Park, Jung Uk Kim, Gyeong-Moon Park |
| 2023 | ICCV | LFS-GAN: Lifelong Few-Shot Image Generation. | Juwon Seo, Ji-Su Kang, Gyeong-Moon Park |
| 2022 | ECCV | IntereStyle: Encoding an Interest Region for Robust StyleGAN Inversion. | Seung Jun Moon, Gyeong-Moon Park |
| 2020 | BMVC | Non-Probabilistic Cosine Similarity Loss for Few-Shot Image Classification. | Joonhyuk Kim, Inug Yoon, Gyeong-Moon Park, Jong-Hwan Kim |
| 2017 | IJCNN | Context preference-based deep adaptive resonance theory: Integrating user preferences into episodic memory encoding and retrieval. | Dick Sigmund, Gyeong-Moon Park, Jong-Hwan Kim |
| 2016 | IJCNN | Deep Adaptive Resonance Theory for learning biologically inspired episodic memory. | Gyeong-Moon Park, Jong-Hwan Kim |
| 2016 | SMC | Biologically-inspired episodic memory model considering the context information. | Gyeong-Moon Park, Sanghyun Cho, Jong-Hwan Kim |