9 citations · 18 across the 12 of their papers we have counts for
6 papers · 1 filter
Video-As-Prompt: Unified Semantic Control for Video Generation
Yuxuan Bian, Xin Chen, Zenan Li +4
Unified, generalizable semantic control in video generation remains a critical open challenge. Existing methods either introduce artifacts by enforcing inappropriate pixel-wise pri…
EditVerse: Unifying Image and Video Editing and Generation with In-Context Learning
Xuan Ju, Tianyu Wang, Yuqian Zhou +11
Recent advances in foundation models highlight a clear trend toward unification and scaling, showing emergent capabilities across diverse domains. While image generation and editin…
VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Control
Yuxuan Bian, Zhaoyang Zhang, Xuan Ju +4
Video inpainting, which aims to restore corrupted video content, has experienced substantial progress. Despite these advances, existing methods, whether propagating unmasked region…
FullDiT: Multi-Task Video Generative Foundation Model with Full Attention
Xuan Ju, Weicai Ye, Quande Liu +6
Current video generative foundation models primarily focus on text-to-video tasks, providing limited control for fine-grained video content creation. Although adapter-based approac…
BrushEdit: All-In-One Image Inpainting and Editing
Yaowei Li, Yuxuan Bian, Xuan Ju +5
Image editing has advanced significantly with the development of diffusion models using both inversion-based and instruction-based methods. However, current inversion-based approac…
MotionCraft: Crafting Whole-Body Motion with Plug-and-Play Multimodal Controls
Yuxuan Bian, Ailing Zeng, Xuan Ju +4
Whole-body multimodal motion generation, controlled by text, speech, or music, has numerous applications including video generation and character animation. However, employing a un…