332 citations · 1.5k across the 59 of their papers we have counts for
6 papers · 1 filter
Word length-aware text spotting: Enhancing detection and recognition in dense text image
Hao Wang, Huabing Zhou, Yanduo Zhang +2
Scene text spotting is essential in various computer vision applications, enabling extracting and interpreting textual information from images. However, existing methods often negl…
Diff-Retinex: Rethinking Low-light Image Enhancement with A Generative Diffusion Model
Xunpeng Yi, Han Xu, Hao Zhang +2
In this paper, we rethink the low-light image enhancement task and propose a physically explainable and generative diffusion model for low-light image enhancement, termed as Diff-R…
ResMatch: Residual Attention Learning for Local Feature Matching
Yuxin Deng, Jiayi Ma
Attention-based graph neural networks have made great progress in feature matching learning. However, insight of how attention mechanism works for feature matching is lacked in the…
Learning Feature Matching via Matchable Keypoint-Assisted Graph Neural Network
Zizhuo Li, Jiayi Ma
Accurately matching local features between a pair of images is a challenging computer vision task. Previous studies typically use attention based graph neural networks (GNNs) with…
Image Deblurring by Exploring In-depth Properties of Transformer
Pengwei Liang, Junjun Jiang, Xianming Liu +1
Image deblurring continues to achieve impressive performance with the development of generative models. Nonetheless, there still remains a displeasing problem if one wants to impro…
Dif-Fusion: Towards High Color Fidelity in Infrared and Visible Image Fusion with Diffusion Models
Jun Yue, Leyuan Fang, Shaobo Xia +2
Color plays an important role in human visual perception, reflecting the spectrum of objects. However, the existing infrared and visible image fusion methods rarely explore how to…