6 papers
Self-NPO: Data-Free Diffusion Model Enhancement via Truncated Diffusion Fine-Tuning
Fu-Yun Wang, Keqiang Sun, Yao Teng +4
Diffusion models have demonstrated remarkable success in various visual generation tasks, including image, video, and 3D content generation. Preference optimization (PO) is a promi…
HPSv3: Towards Wide-Spectrum Human Preference Score
Yuhang Ma, Yunhao Shui, Xiaoshi Wu +2
Evaluating text-to-image generation models requires alignment with human perception, yet existing human-centric metrics are constrained by limited data coverage, suboptimal feature…
Diffusion-NPO: Negative Preference Optimization for Better Preference Aligned Generation of Diffusion Models
Fu-Yun Wang, Yunhao Shui, Jingtan Piao +2
Diffusion models have made substantial advances in image generation, yet models trained on large, unfiltered datasets often yield outputs misaligned with human preferences. Numerou…
BlinkVision: A Benchmark for Optical Flow, Scene Flow and Point Tracking Estimation using RGB Frames and Events
Yijin Li, Yichen Shen, Zhaoyang Huang +9
Recent advances in event-based vision suggest that these systems complement traditional cameras by providing continuous observation without frame rate limitations and a high dynami…
Phased Consistency Models
Fu-Yun Wang, Zhaoyang Huang, Alexander William Bergman +9
Consistency Models (CMs) have made significant progress in accelerating the generation of diffusion models. However, their application to high-resolution, text-conditioned image ge…
AnimateLCM: Computation-Efficient Personalized Style Video Generation without Personalized Video Data
Fu-Yun Wang, Zhaoyang Huang, Weikang Bian +5
This paper introduces an effective method for computation-efficient personalized style video generation without requiring access to any personalized video data. It reduces the nece…