collaborators

7 papers

cs.CV2026

Instruction-Based Video Editing by Repurposing an Image Editing Model

Yunpeng Bai, Yossi Gandelsman, Michaël Gharbi +1

Instruction-based video editing is commonly built on video-pretrained generative backbones: a video diffusion transformer is adapted, at considerable cost, to condition on a source…

cs.CV2026

DuSPiT: Dual-Branch Sub-Patch Pixel Diffusion Transformer

Yunpeng Bai, Yossi Gandelsman, Michaël Gharbi

Diffusion Transformers achieve strong image generation performance, but most operate in compressed latent spaces. Pixel-space diffusion avoids this information loss, yet existing a…

cs.CV2026

PE-Field 4D: Video Generation Models as Canvas

Yunpeng Bai, Haoxiang Li, Qixing Huang

Diffusion Transformers have recently achieved strong performance in video generation, yet controlling scene geometry under viewpoint changes and camera motion remains challenging.…

cs.CV2025

WorldReel: 4D Video Generation with Consistent Geometry and Motion Modeling

Shaoheng Fang, Hanwen Jiang, Yunpeng Bai +2

Recent video generators achieve striking photorealism, yet remain fundamentally inconsistent in 3D. We present WorldReel, a 4D video generator that is natively spatio-temporally co…

cs.CV2025

GeoVideo: Introducing Geometric Regularization into Video Generation Model

Yunpeng Bai, Shaoheng Fang, Chaohui Yu +2

Recent advances in video generation have enabled the synthesis of high-quality and visually realistic clips using diffusion transformer models. However, most existing approaches op…

cs.CV2025

Positional Encoding Field

Yunpeng Bai, Haoxiang Li, Qixing Huang

Diffusion Transformers (DiTs) have emerged as the dominant architecture for visual generation, powering state-of-the-art image and video models. By representing images as patch tok…