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NightHazeFormer: Single Nighttime Haze Removal Using Prior Query Transformer
Yun Liu, Zhongsheng Yan, Sixiang Chen +3
Nighttime image dehazing is a challenging task due to the presence of multiple types of adverse degrading effects including glow, haze, blurry, noise, color distortion, and so on.…
SCANet: Self-Paced Semi-Curricular Attention Network for Non-Homogeneous Image Dehazing
Yu Guo, Yuan Gao, Ryan Wen Liu +4
The presence of non-homogeneous haze can cause scene blurring, color distortion, low contrast, and other degradations that obscure texture details. Existing homogeneous dehazing me…
Unpaired Overwater Image Defogging Using Prior Map Guided CycleGAN
Yaozong Mo, Chaofeng Li, Wenqi Ren +3
Deep learning-based methods have achieved significant performance for image defogging. However, existing methods are mainly developed for land scenes and perform poorly when dealin…
Towards Generalization on Real Domain for Single Image Dehazing via Meta-Learning
Wenqi Ren, Qiyu Sun, Chaoqiang Zhao +1
Learning-based image dehazing methods are essential to assist autonomous systems in enhancing reliability. Due to the domain gap between synthetic and real domains, the internal in…
Visual Semantic Segmentation Based on Few/Zero-Shot Learning: An Overview
Wenqi Ren, Yang Tang, Qiyu Sun +2
Visual semantic segmentation aims at separating a visual sample into diverse blocks with specific semantic attributes and identifying the category for each block, and it plays a cr…
Cylin-Painting: Seamless {360\textdegree} Panoramic Image Outpainting and Beyond
Kang Liao, Xiangyu Xu, Chunyu Lin +3
Image outpainting gains increasing attention since it can generate the complete scene from a partial view, providing a valuable solution to construct {360\textdegree} panoramic ima…
High-resolution Iterative Feedback Network for Camouflaged Object Detection
Xiaobin Hu, Shuo Wang, Xuebin Qin +5
Spotting camouflaged objects that are visually assimilated into the background is tricky for both object detection algorithms and humans who are usually confused or cheated by the…
Deep Image Deblurring: A Survey
Kaihao Zhang, Wenqi Ren, Wenhan Luo +4
Image deblurring is a classic problem in low-level computer vision with the aim to recover a sharp image from a blurred input image. Advances in deep learning have led to significa…
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 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…
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…
Face Super-Resolution Guided by 3D Facial Priors
Xiaobin Hu, Wenqi Ren, John LaMaster +5
State-of-the-art face super-resolution methods employ deep convolutional neural networks to learn a mapping between low- and high- resolution facial patterns by exploring local app…
Domain Adaptation for Image Dehazing
Yuanjie Shao, Lerenhan Li, Wenqi Ren +2
Image dehazing using learning-based methods has achieved state-of-the-art performance in recent years. However, most existing methods train a dehazing model on synthetic hazy image…
DCNAS: Densely Connected Neural Architecture Search for Semantic Image Segmentation
Xiong Zhang, Hongmin Xu, Hong Mo +4
Neural Architecture Search (NAS) has shown great potentials in automatically designing scalable network architectures for dense image predictions. However, existing NAS algorithms…
UG Track 2: A Collective Benchmark Effort for Evaluating and Advancing Image Understanding in Poor Visibility Environments
Ye Yuan, Wenhan Yang, Wenqi Ren +3
The UG challenge in IEEE CVPR 2019 aims to evoke a comprehensive discussion and exploration about how low-level vision techniques can benefit the high-level automatic visual…
Single Image Deraining: A Comprehensive Benchmark Analysis
Siyuan Li, Iago Breno Araujo, Wenqi Ren +7
We present a comprehensive study and evaluation of existing single image deraining algorithms, using a new large-scale benchmark consisting of both synthetic and real-world rainy i…