CVPR "denoising process" Papers
5 papers found
FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less Compute
Sotiris Anagnostidis, Gregor Bachmann, Yeongmin Kim et al.
CVPR 2025highlightarXiv:2502.20126
5
citations
Make It Count: Text-to-Image Generation with an Accurate Number of Objects
Lital Binyamin, Yoad Tewel, Hilit Segev et al.
CVPR 2025posterarXiv:2406.10210
32
citations
Not All Parameters Matter: Masking Diffusion Models for Enhancing Generation Ability
Lei Wang, Senmao Li, Fei Yang et al.
CVPR 2025posterarXiv:2505.03097
2
citations
Pioneering 4-Bit FP Quantization for Diffusion Models: Mixup-Sign Quantization and Timestep-Aware Fine-Tuning
Maosen Zhao, Pengtao Chen, Chong Yu et al.
CVPR 2025posterarXiv:2505.21591
3
citations
VideoGuide: Improving Video Diffusion Models without Training Through a Teacher's Guide
Dohun Lee, Bryan Sangwoo Kim, Geon Yeong Park et al.
CVPR 2025posterarXiv:2410.04364
2
citations