45 citations · 108 across the 10 of their papers we have counts for
10 papers
LUT-GCE: Lookup Table Global Curve Estimation for Fast Low-light Image Enhancement
Changguang Wu, Jiangxin Dong, Jinhui Tang
We present an effective and efficient approach for low-light image enhancement, named Lookup Table Global Curve Estimation (LUT-GCE). In contrast to existing curve-based methods wi…
Multi-Granularity Denoising and Bidirectional Alignment for Weakly Supervised Semantic Segmentation
Tao Chen, Yazhou Yao, Jinhui Tang
Weakly supervised semantic segmentation (WSSS) models relying on class activation maps (CAMs) have achieved desirable performance comparing to the non-CAMs-based counterparts. Howe…
VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset
Jing Liu, Sihan Chen, Xingjian He +4
In this paper, we propose a Vision-Audio-Language Omni-peRception pretraining model (VALOR) for multi-modal understanding and generation. Different from widely-studied vision-langu…
Semantic Scene Completion with Cleaner Self
Fengyun Wang, Dong Zhang, Hanwang Zhang +2
Semantic Scene Completion (SSC) transforms an image of single-view depth and/or RGB 2D pixels into 3D voxels, each of whose semantic labels are predicted. SSC is a well-known ill-p…
Spatially-Adaptive Feature Modulation for Efficient Image Super-Resolution
Long Sun, Jiangxin Dong, Jinhui Tang +1
Although numerous solutions have been proposed for image super-resolution, they are usually incompatible with low-power devices with many computational and memory constraints. In t…
DLGSANet: Lightweight Dynamic Local and Global Self-Attention Networks for Image Super-Resolution
Xiang Li, Jinshan Pan, Jinhui Tang +1
We propose an effective lightweight dynamic local and global self-attention network (DLGSANet) to solve image super-resolution. Our method explores the properties of Transformers w…
BiSTNet: Semantic Image Prior Guided Bidirectional Temporal Feature Fusion for Deep Exemplar-based Video Colorization
Yixin Yang, Zhongzheng Peng, Xiaoyu Du +3
How to effectively explore the colors of reference exemplars and propagate them to colorize each frame is vital for exemplar-based video colorization. In this paper, we present an…
SLLEN: Semantic-aware Low-light Image Enhancement Network
Mingye Ju, Chuheng Chen, Charles A. Guo +3
How to effectively explore semantic feature is vital for low-light image enhancement (LLE). Existing methods usually utilize the semantic feature that is only drawn from the output…
Accurate and Efficient Stereo Matching via Attention Concatenation Volume
Gangwei Xu, Yun Wang, Junda Cheng +2
Stereo matching is a fundamental building block for many vision and robotics applications. An informative and concise cost volume representation is vital for stereo matching of hig…
Understanding the Tricks of Deep Learning in Medical Image Segmentation: Challenges and Future Directions
Dong Zhang, Yi Lin, Hao Chen +4
Over the past few years, the rapid development of deep learning technologies for computer vision has significantly improved the performance of medical image segmentation (MedISeg).…