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MC-Blur: A Comprehensive Benchmark for Image Deblurring
Kaihao Zhang, Tao Wang, Wenhan Luo +6
Blur artifacts can seriously degrade the visual quality of images, and numerous deblurring methods have been proposed for specific scenarios. However, in most real-world images, bl…
A survey on computational spectral reconstruction methods from RGB to hyperspectral imaging
Jingang Zhang, Runmu Su, Wenqi Ren +3
Hyperspectral imaging enables versatile applications due to its competence in capturing abundant spatial and spectral information, which are crucial for identifying substances. How…
A Comprehensive Survey and Taxonomy on Single Image Dehazing Based on Deep Learning
Jie Gui, Xiaofeng Cong, Yuan Cao +5
With the development of convolutional neural networks, hundreds of deep learning based dehazing methods have been proposed. In this paper, we provide a comprehensive survey on supe…
Beyond Monocular Deraining: Parallel Stereo Deraining Network Via Semantic Prior
Kaihao Zhang, Wenhan Luo, Yanjiang Yu +6
Rain is a common natural phenomenon. Taking images in the rain however often results in degraded quality of images, thus compromises the performance of many computer vision systems…
Reciprocal Feature Learning via Explicit and Implicit Tasks in Scene Text Recognition
Hui Jiang, Yunlu Xu, Zhanzhan Cheng +5
Text recognition is a popular topic for its broad applications. In this work, we excavate the implicit task, character counting within the traditional text recognition, without add…
LGPMA: Complicated Table Structure Recognition with Local and Global Pyramid Mask Alignment
Liang Qiao, Zaisheng Li, Zhanzhan Cheng +6
Table structure recognition is a challenging task due to the various structures and complicated cell spanning relations. Previous methods handled the problem starting from elements…
Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding
Chongyi Li, Saeed Anwar, Junhui Hou +3
Underwater images suffer from color casts and low contrast due to wavelength- and distance-dependent attenuation and scattering. To solve these two degradation issues, we present a…
Progressive residual learning for single image dehazing
Yudong Liang, Bin Wang, Jiaying Liu +3
The recent physical model-free dehazing methods have achieved state-of-the-art performances. However, without the guidance of physical models, the performances degrade rapidly when…
ARVo: Learning All-Range Volumetric Correspondence for Video Deblurring
Dongxu Li, Chenchen Xu, Kaihao Zhang +5
Video deblurring models exploit consecutive frames to remove blurs from camera shakes and object motions. In order to utilize neighboring sharp patches, typical methods rely mainly…
Enhanced Spatio-Temporal Interaction Learning for Video Deraining: A Faster and Better Framework
Kaihao Zhang, Dongxu Li, Wenhan Luo +2
Video deraining is an important task in computer vision as the unwanted rain hampers the visibility of videos and deteriorates the robustness of most outdoor vision systems. Despit…
Dual Attention-in-Attention Model for Joint Rain Streak and Raindrop Removal
Kaihao Zhang, Dongxu Li, Wenhan Luo +1
Rain streaks and rain drops are two natural phenomena, which degrade image capture in different ways. Currently, most existing deep deraining networks take them as two distinct pro…
Self-Supervised Noisy Label Learning for Source-Free Unsupervised Domain Adaptation
Weijie Chen, Luojun Lin, Shicai Yang +4
It is a strong prerequisite to access source data freely in many existing unsupervised domain adaptation approaches. However, source data is agnostic in many practical scenarios du…
Progressive Depth Learning for Single Image Dehazing
Yudong Liang, Bin Wang, Jiaying Liu +3
The formulation of the hazy image is mainly dominated by the reflected lights and ambient airlight. Existing dehazing methods often ignore the depth cues and fail in distant areas…