9.2k citations · 16.2k across the 175 of their papers we have counts for
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Invertible Network for Unpaired Low-light Image Enhancement
Jize Zhang, Haolin Wang, Xiaohe Wu +1
Existing unpaired low-light image enhancement approaches prefer to employ the two-way GAN framework, in which two CNN generators are deployed for enhancement and degradation separa…
Local Patch Network with Global Attention for Infrared Small Target Detection
Fang Chen, Chenqiang Gao, Fangcen Liu +4
Infrared small target detection plays an important role in the infrared search and tracking applications. In recent years, deep learning techniques were introduced to this task and…
Infrared Small-Dim Target Detection with Transformer under Complex Backgrounds
Fangcen Liu, Chenqiang Gao, Fang Chen +3
The infrared small-dim target detection is one of the key techniques in the infrared search and tracking system. Since the local regions similar to infrared small-dim targets sprea…
Learning RAW-to-sRGB Mappings with Inaccurately Aligned Supervision
Zhilu Zhang, Haolin Wang, Ming Liu +3
Learning RAW-to-sRGB mapping has drawn increasing attention in recent years, wherein an input raw image is trained to imitate the target sRGB image captured by another camera. Howe…
Variational Attention: Propagating Domain-Specific Knowledge for Multi-Domain Learning in Crowd Counting
Binghui Chen, Zhaoyi Yan, Ke Li +4
In crowd counting, due to the problem of laborious labelling, it is perceived intractability of collecting a new large-scale dataset which has plentiful images with large diversity…
Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation
Yuxiang Wei, Yupeng Shi, Xiao Liu +4
Unsupervised disentanglement learning is a crucial issue for understanding and exploiting deep generative models. Recently, SeFa tries to find latent disentangled directions by per…
Boosting Weakly Supervised Object Detection via Learning Bounding Box Adjusters
Bowen Dong, Zitong Huang, Yuelin Guo +3
Weakly-supervised object detection (WSOD) has emerged as an inspiring recent topic to avoid expensive instance-level object annotations. However, the bounding boxes of most existin…
Crowd Counting via Perspective-Guided Fractional-Dilation Convolution
Zhaoyi Yan, Ruimao Zhang, Hongzhi Zhang +2
Crowd counting is critical for numerous video surveillance scenarios. One of the main issues in this task is how to handle the dramatic scale variations of pedestrians caused by th…
Image Inpainting with Edge-guided Learnable Bidirectional Attention Maps
Dongsheng Wang, Chaohao Xie, Shaohui Liu +2
For image inpainting, the convolutional neural networks (CNN) in previous methods often adopt standard convolutional operator, which treats valid pixels and holes indistinguishably…
Learning Semantic Person Image Generation by Region-Adaptive Normalization
Zhengyao Lv, Xiaoming Li, Xin Li +4
Human pose transfer has received great attention due to its wide applications, yet is still a challenging task that is not well solved. Recent works have achieved great success to…
Learning Scalable -constrained Near-lossless Image Compression via Joint Lossy Image and Residual Compression
Yuanchao Bai, Xianming Liu, Wangmeng Zuo +2
We propose a novel joint lossy image and residual compression framework for learning -constrained near-lossless image compression. Specifically, we obtain a lossy reco…
Asymmetric CNN for image super-resolution
Chunwei Tian, Yong Xu, Wangmeng Zuo +2
Deep convolutional neural networks (CNNs) have been widely applied for low-level vision over the past five years. According to nature of different applications, designing appropria…
Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser
Yue Cao, Xiaohe Wu, Shuran Qi +3
The success of deep denoisers on real-world color photographs usually relies on the modeling of sensor noise and in-camera signal processing (ISP) pipeline. Performance drop will i…
Deepfake Forensics via An Adversarial Game
Zhi Wang, Yiwen Guo, Wangmeng Zuo
With the progress in AI-based facial forgery (i.e., deepfake), people are increasingly concerned about its abuse. Albeit effort has been made for training classification (also know…
Learning Class-Agnostic Pseudo Mask Generation for Box-Supervised Semantic Segmentation
Chaohao Xie, Dongwei Ren, Lei Wang +1
Recently, several weakly supervised learning methods have been devoted to utilize bounding box supervision for training deep semantic segmentation models. Most existing methods usu…
Localization Distillation for Dense Object Detection
Zhaohui Zheng, Rongguang Ye, Ping Wang +4
Knowledge distillation (KD) has witnessed its powerful capability in learning compact models in object detection. Previous KD methods for object detection mostly focus on imitating…
Self Sparse Generative Adversarial Networks
Wenliang Qian, Yang Xu, Wangmeng Zuo +1
Generative Adversarial Networks (GANs) are an unsupervised generative model that learns data distribution through adversarial training. However, recent experiments indicated that G…
Hybrid Trilinear and Bilinear Programming for Aligning Partially Overlapping Point Sets
Wei Lian, Wangmeng Zuo
In many applications, we need algorithms which can align partially overlapping point sets and are invariant to the corresponding transformations. In this work, a method possessing…