ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models J Choi, S Kim, Y Jeong, Y Gwon, S Yoon ICCV 2021 (arXiv preprint arXiv:2108.02938), 2021 | 456* | 2021 |
Perception Prioritized Training of Diffusion Models J Choi, J Lee, C Shin, S Kim, H Kim, S Yoon CVPR 2022 (arXiv preprint arXiv:2204.00227), 2022 | 126 | 2022 |
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation J Lee, J Choi, J Mok, S Yoon NeurIPS 2021 (arXiv preprint arXiv:2110.06530), 2021 | 124 | 2021 |
Custom-Edit: Text-Guided Image Editing with Customized Diffusion Models J Choi, Y Choi, Y Kim, J Kim, S Yoon CVPR 2023 AI4CC Workshop (arXiv preprint arXiv:2305.15779), 2023 | 19 | 2023 |
Toward Spatially Unbiased Generative Models J Choi, J Lee, Y Jeong, S Yoon ICCV 2021 (arXiv preprint arXiv:2108.01285), 2021 | 14 | 2021 |
FICGAN: facial identity controllable GAN for de-identification Y Jeong, J Choi, S Kim, Y Ro, TH Oh, D Kim, H Ha, S Yoon arXiv preprint arXiv:2110.00740, 2021 | 12 | 2021 |
Diffusion-stego: Training-free diffusion generative steganography via message projection D Kim, C Shin, J Choi, D Jung, S Yoon arXiv preprint arXiv:2305.18726, 2023 | 4 | 2023 |
Simple Drop-in LoRA Conditioning on Attention Layers Will Improve Your Diffusion Model JY Choi, JR Park, I Park, J Cho, A No, EK Ryu arXiv preprint arXiv:2405.03958, 2024 | | 2024 |
Efficient Diffusion-Driven Corruption Editor for Test-Time Adaptation Y Oh, J Lee, J Choi, D Jung, U Hwang, S Yoon arXiv preprint arXiv:2403.10911, 2024 | | 2024 |
Improving Diffusion-Based Generative Models via Approximated Optimal Transport D Kim, J Choi, C Shin, U Hwang, S Yoon arXiv preprint arXiv:2403.05069, 2024 | | 2024 |
ControlDreamer: Stylized 3D Generation with Multi-View ControlNet Y Oh, J Choi, Y Kim, M Park, C Shin, S Yoon arXiv preprint arXiv:2312.01129, 2023 | | 2023 |