3 papers
cs.CV2026
Bend the Basics: Degradation-Aware Deformable Tokenization for All-in-One Image Restoration
Zihao He, Yunfeng Wu, Xinchao Wang +1
All-in-one image restoration seeks a single model that can recover images degraded by diverse and spatially non-uniform corruptions. However, many unified Transformers rely on fixe…
cs.CV2026
ViBe: Ultra-High-Resolution Video Synthesis Born from Pure Images
Yunfeng Wu, Hongying Cheng, Zihao He +1
Transformer-based video diffusion models rely on 3D attention over spatial and temporal tokens, which incurs quadratic time and memory complexity and makes end-to-end training for…
cs.CV2025
FreeSwim: Revisiting Sliding-Window Attention Mechanisms for Training-Free Ultra-High-Resolution Video Generation
Yunfeng Wu, Jiayi Song, Zhenxiong Tan +2
The quadratic time and memory complexity of the attention mechanism in modern Transformer based video generators makes end-to-end training for ultra high resolution videos prohibit…