7 papers · 1 filter
CompareBench: A Benchmark for Visual Comparison Reasoning in Vision-Language Models
Jie Cai, Kangning Yang, Lan Fu +6
We introduce CompareBench, a benchmark for evaluating visual comparison reasoning in vision-language models (VLMs), a fundamental yet understudied skill. CompareBench consists of 1…
OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal
Kangning Yang, Ling Ouyang, Huiming Sun +5
Reflection removal technology plays a crucial role in photography and computer vision applications. However, existing techniques are hindered by the lack of high-quality in-the-wil…
F2T2-HiT: A U-Shaped FFT Transformer and Hierarchical Transformer for Reflection Removal
Jie Cai, Kangning Yang, Ling Ouyang +5
Single Image Reflection Removal (SIRR) technique plays a crucial role in image processing by eliminating unwanted reflections from the background. These reflections, often caused b…
OpenRR-5k: A Large-Scale Benchmark for Reflection Removal in the Wild
Jie Cai, Kangning Yang, Ling Ouyang +4
Removing reflections is a crucial task in computer vision, with significant applications in photography and image enhancement. Nevertheless, existing methods are constrained by the…
Degradation-Aware Image Enhancement via Vision-Language Classification
Jie Cai, Kangning Yang, Jiaming Ding +5
Image degradation is a prevalent issue in various real-world applications, affecting visual quality and downstream processing tasks. In this study, we propose a novel framework tha…
VIP: Video Inpainting Pipeline for Real World Human Removal
Huiming Sun, Yikang Li, Kangning Yang +11
Inpainting for real-world human and pedestrian removal in high-resolution video clips presents significant challenges, particularly in achieving high-quality outcomes, ensuring tem…