9 papers
SeFi-Image: A Text-to-Image Foundation Model with Semantic-First Diffusion
Ruoyu Feng, Jinming Liu, Yuqi Wang +7
Training image generation foundation models consumes substantial resources. Previous methods have attempted to leverage semantic guidance to accelerate the training process, yet th…
Bridging Video Understanding and Generation in a Unified Framework
Yuqi Wang, Runyi Li, Ruoyu Feng +3
Recently, unified image generation and understanding have been extensively explored. However, extending such unified modeling paradigms to the video domain remains largely underexp…
The 1st PortraitCraft Challenge: A CVPR 2026 Workshop Competition on Portrait Composition Understanding and Generation
Zijie Lou, Youyun Tang, Xiaochao Qu +40
This paper presents an overview of the inaugural PortraitCraft Challenge, held as one of the official competitions at CVPR 2026. The challenge focuses on portrait composition under…
Semantics Lead the Way: Harmonizing Semantic and Texture Modeling with Asynchronous Latent Diffusion
Yueming Pan, Ruoyu Feng, Qi Dai +5
Latent Diffusion Models (LDMs) inherently follow a coarse-to-fine generation process, where high-level semantic structure is generated slightly earlier than fine-grained texture. T…
LVFace: Progressive Cluster Optimization for Large Vision Models in Face Recognition
Jinghan You, Shanglin Li, Yuanrui Sun +4
Vision Transformers (ViTs) have revolutionized large-scale visual modeling, yet remain underexplored in face recognition (FR) where CNNs still dominate. We identify a critical bott…
ContentV: Efficient Training of Video Generation Models with Limited Compute
Wenfeng Lin, Renjie Chen, Boyuan Liu +10
Recent advances in video generation demand increasingly efficient training recipes to mitigate escalating computational costs. In this report, we present ContentV, an 8B-parameter…