BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance Segmentation. - Jungbeom Lee; Jihun Yi; Chaehun Shin; Sungroh Yoon (CVPR, 2021)

Personalized Face Authentication Based On Few-Shot Meta-Learning. - Chaehun Shin; Jangho Lee 002; Byunggook Na; Sungroh Yoon (ICIP, 2021)

PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Driven Adaptive Prior. - Sang-gil Lee; Heeseung Kim; Chaehun Shin; Xu Tan 003; Chang Liu 030; Qi Meng; Tao Qin 001; Wei Chen 034; Sungroh Yoon; Tie-Yan Liu (CoRR, 2021)

Perception Prioritized Training of Diffusion Models. - Jooyoung Choi; Jungbeom Lee; Chaehun Shin; Sungwon Kim 001; Hyunwoo Kim; Sungroh Yoon (CVPR, 2022)

PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior. - Sang-gil Lee; Heeseung Kim; Chaehun Shin; Xu Tan 003; Chang Liu 030; Qi Meng; Tao Qin 001; Wei Chen 034; Sungroh Yoon; Tie-Yan Liu (ICLR, 2022)

Out of Sight, Out of Mind: A Source-View-Wise Feature Aggregation for Multi-View Image-Based Rendering. - Geonho Cha; Chaehun Shin; Sungroh Yoon; Dongyoon Wee (CoRR, 2022)

Edit-A-Video: Single Video Editing with Object-Aware Consistency. - Chaehun Shin; Heeseung Kim; Che Hyun Lee; Sang-gil Lee; Sungroh Yoon (ACML, 2023)

ControlDreamer: Stylized 3D Generation with Multi-View ControlNet. - Yeongtak Oh; Jooyoung Choi; Yongsung Kim; Minjun Park; Chaehun Shin; Sungroh Yoon (CoRR, 2023)

ControlDreamer: Blending Geometry and Style in Text-to-3D. - Yeongtak Oh; Jooyoung Choi; Yongsung Kim; Minjun Park; Chaehun Shin; Sungroh Yoon (BMVC, 2024)

Improving Diffusion-Based Generative Models via Approximated Optimal Transport. - Daegyu Kim; Jooyoung Choi; Chaehun Shin; Uiwon Hwang; Sungroh Yoon (CoRR, 2024)

Style-Friendly SNR Sampler for Style-Driven Generation. - Jooyoung Choi; Chaehun Shin; Yeongtak Oh; Heeseung Kim; Sungroh Yoon (CoRR, 2024)

Disentangled Motion Modeling for Video Frame Interpolation. - Jaihyun Lew; Jooyoung Choi; Chaehun Shin; Dahuin Jung; Sungroh Yoon (AAAI, 2025)

Large-Scale Text-to-Image Model with Inpainting is a Zero-Shot Subject-Driven Image Generator. - Chaehun Shin; Jooyoung Choi; Heeseung Kim; Sungroh Yoon (CVPR, 2025)

Diffusion-Stego: Training-free diffusion generative steganography via message projection. - Daegyu Kim; Chaehun Shin; Jooyoung Choi; Dahuin Jung; Sungroh Yoon (Inf. Sci., 2025)

Negative-Guided Subject Fidelity Optimization for Zero-Shot Subject-Driven Generation. - Chaehun Shin; Jooyoung Choi; Johan Barthelemy; Jungbeom Lee; Sungroh Yoon (CoRR, 2025)