89 citations · 137 across the 16 of their papers we have counts for
8 papers · 1 filter
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…
Stable Consistency Tuning: Understanding and Improving Consistency Models
Fu-Yun Wang, Zhengyang Geng, Hongsheng Li
Diffusion models achieve superior generation quality but suffer from slow generation speed due to the iterative nature of denoising. In contrast, consistency models, a new generati…
Lumina-Next: Making Lumina-T2X Stronger and Faster with Next-DiT
Le Zhuo, Ruoyi Du, Han Xiao +19
Lumina-T2X is a nascent family of Flow-based Large Diffusion Transformers that establishes a unified framework for transforming noise into various modalities, such as images and vi…
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…
Rethinking the Spatial Inconsistency in Classifier-Free Diffusion Guidance
Dazhong Shen, Guanglu Song, Zeyue Xue +2
Classifier-Free Guidance (CFG) has been widely used in text-to-image diffusion models, where the CFG scale is introduced to control the strength of text guidance on the whole image…
Be-Your-Outpainter: Mastering Video Outpainting through Input-Specific Adaptation
Fu-Yun Wang, Xiaoshi Wu, Zhaoyang Huang +5
Video outpainting is a challenging task, aiming at generating video content outside the viewport of the input video while maintaining inter-frame and intra-frame consistency. Exist…
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…
Motion-I2V: Consistent and Controllable Image-to-Video Generation with Explicit Motion Modeling
Xiaoyu Shi, Zhaoyang Huang, Fu-Yun Wang +9
We introduce Motion-I2V, a novel framework for consistent and controllable image-to-video generation (I2V). In contrast to previous methods that directly learn the complicated imag…