12 citations · 14 across the 6 of their papers we have counts for
8 papers · 1 filter
Wan-Image: Pushing the Boundaries of Generative Visual Intelligence
Chaojie Mao, Chen-Wei Xie, Chongyang Zhong +55
We present Wan-Image, a unified visual generation system explicitly engineered to paradigm-shift image generation models from casual synthesizers into professional-grade productivi…
Wan-Weaver: Interleaved Multi-modal Generation via Decoupled Training
Jinbo Xing, Zeyinzi Jiang, Yuxiang Tuo +15
Recent unified models have made unprecedented progress in both understanding and generation. However, while most of them accept multi-modal inputs, they typically produce only sing…
Wan: Open and Advanced Large-Scale Video Generative Models
Team Wan, Ang Wang, Baole Ai +58
This report presents Wan, a comprehensive and open suite of video foundation models designed to push the boundaries of video generation. Built upon the mainstream diffusion transfo…
VACE: All-in-One Video Creation and Editing
Zeyinzi Jiang, Zhen Han, Chaojie Mao +3
Diffusion Transformer has demonstrated powerful capability and scalability in generating high-quality images and videos. Further pursuing the unification of generation and editing…
ICE-Bench: A Unified and Comprehensive Benchmark for Image Creating and Editing
Yulin Pan, Xiangteng He, Chaojie Mao +4
Image generation has witnessed significant advancements in the past few years. However, evaluating the performance of image generation models remains a formidable challenge. In thi…
ACE++: Instruction-Based Image Creation and Editing via Context-Aware Content Filling
Chaojie Mao, Jingfeng Zhang, Yulin Pan +4
We report ACE++, an instruction-based diffusion framework that tackles various image generation and editing tasks. Inspired by the input format for the inpainting task proposed by…