6 papers
YOSE: You Only Select Essential Tokens for Efficient DiT-based Video Object Removal
Chenyang Wu, Lina Lei, Fan Li +6
Recent advances in Diffusion Transformer (DiT)-based video generation technologies have shown impressive results for video object removal. However, these methods still suffer from…
Mixture of Style Experts for Diverse Image Stylization
Shihao Zhu, Ziheng Ouyang, Yijia Kang +5
Diffusion-based stylization has advanced significantly, yet existing methods are limited to color-driven transformations, neglecting complex semantics and material details. We intr…
Time-Aware One Step Diffusion Network for Real-World Image Super-Resolution
Tianyi Zhang, Zheng-Peng Duan, Peng-Tao Jiang +4
Diffusion-based real-world image super-resolution (Real-ISR) methods have demonstrated impressive performance.To achieve efficient Real-ISR, many works employ Variational Score Dis…
FlowConsist: Make Your Flow Consistent with Real Trajectory
Tianyi Zhang, Chengcheng Liu, Jinwei Chen +5
Fast flow models accelerate the iterative sampling process by learning to directly predict ODE path integrals, enabling one-step or few-step generation. However, we argue that curr…
Infinite-World: Scaling Interactive World Models to 1000-Frame Horizons via Pose-Free Hierarchical Memory
Ruiqi Wu, Xuanhua He, Meng Cheng +8
We propose Infinite-World, a robust interactive world model capable of maintaining coherent visual memory over 1000+ frames in complex real-world environments. While existing world…
RAM++: Robust Representation Learning via Adaptive Mask for All-in-One Image Restoration
Zilong Zhang, Chujie Qin, Chunle Guo +4
This work presents Robust Representation Learning via Adaptive Mask (RAM++), a two-stage framework for all-in-one image restoration. RAM++ integrates high-level semantic understand…