9 citations · 21 across the 14 of their papers we have counts for
12 papers · 1 filter
Self Gradient Forcing: Native Long Video Extrapolation
Junhao Zhuang, Shiyi Zhang, Yuxuan Bian +11
Recent autoregressive video diffusion methods are increasingly built upon Self Forcing, where the student is trained on histories produced by its own rollout rather than ground-tru…
Ultra Flash: Scaling Real-Time Streaming Video Generation to High Resolutions
Xin Lu, Luxury, Jie Huang +27
While recent autoregressive video diffusion models achieve remarkable streaming quality, they remain confined to low resolutions (e.g., 480P), leaving efficient, scalable, real-tim…
Echo-Memory: A Controlled Study of Memory in Action World Models
Wayne King, Zeyue Xue, Yuxuan Bian +13
We present \textbf{Echo-Memory}, a controlled study of memory mechanisms in action-conditioned world models. These models generate multi-segment videos from a first frame, text pro…
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…
OmniMotion-X: Versatile Multimodal Whole-Body Motion Generation
Guowei Xu, Yuxuan Bian, Ailing Zeng +6
This paper introduces OmniMotion-X, a versatile multimodal framework for whole-body human motion generation, leveraging an autoregressive diffusion transformer in a unified sequenc…
IC-Custom: Diverse Image Customization via In-Context Learning
Yaowei Li, Xiaoyu Li, Zhaoyang Zhang +11
Image customization, a crucial technique for industrial media production, aims to generate content that is consistent with reference images. However, current approaches conventiona…
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…
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…
Image Inpainting Models are Effective Tools for Instruction-guided Image Editing
Xuan Ju, Junhao Zhuang, Zhaoyang Zhang +3
This is the technique report for the winning solution of the CVPR2024 GenAI Media Generation Challenge Workshop's Instruction-guided Image Editing track. Instruction-guided image e…
BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion
Xuan Ju, Xian Liu, Xintao Wang +3
Image inpainting, the process of restoring corrupted images, has seen significant advancements with the advent of diffusion models (DMs). Despite these advancements, current DM ada…
Direct Inversion: Boosting Diffusion-based Editing with 3 Lines of Code
Xuan Ju, Ailing Zeng, Yuxuan Bian +2
Text-guided diffusion models have revolutionized image generation and editing, offering exceptional realism and diversity. Specifically, in the context of diffusion-based editing,…