11 papers
FlowPainter: Inpainting Optical Flow via Confidence-Guided Completion
Yuang Meng, Chenyang Wu, Xianshun Liu +7
Existing optical flow methods broadly follow two paradigms: iterative optimization and diffusion-based estimation. Iterative methods, exemplified by RAFT, achieve high accuracy thr…
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…
PerTouch: VLM-Driven Agent for Personalized and Semantic Image Retouching
Zewei Chang, Zheng-Peng Duan, Jianxing Zhang +6
Image retouching aims to enhance visual quality while aligning with users' personalized aesthetic preferences. To address the challenge of balancing controllability and subjectivit…
VTinker: Guided Flow Upsampling and Texture Mapping for High-Resolution Video Frame Interpolation
Chenyang Wu, Jiayi Fu, Chun-Le Guo +2
Due to large pixel movement and high computational cost, estimating the motion of high-resolution frames is challenging. Thus, most flow-based Video Frame Interpolation (VFI) metho…
DetectAnyLLM: Towards Generalizable and Robust Detection of Machine-Generated Text Across Domains and Models
Jiachen Fu, Chun-Le Guo, Chongyi Li
The rapid advancement of large language models (LLMs) has drawn urgent attention to the task of machine-generated text detection (MGTD). However, existing approaches struggle in co…