159 citations · 943 across the 39 of their papers we have counts for
10 papers · 1 filter
TAGPerson: A Target-Aware Generation Pipeline for Person Re-identification
Kai Chen, Weihua Chen, Tao He +5
Nowadays, real data in person re-identification (ReID) task is facing privacy issues, e.g., the banned dataset DukeMTMC-ReID. Thus it becomes much harder to collect real data for R…
RepMLPNet: Hierarchical Vision MLP with Re-parameterized Locality
Xiaohan Ding, Honghao Chen, Xiangyu Zhang +2
Compared to convolutional layers, fully-connected (FC) layers are better at modeling the long-range dependencies but worse at capturing the local patterns, hence usually less favor…
LODE: Deep Local Deblurring and A New Benchmark
Zerun Wang, Liuyu Xiang, Fan Yang +6
While recent deep deblurring algorithms have achieved remarkable progress, most existing methods focus on the global deblurring problem, where the image blur mostly arises from sev…
Emotion Recognition from Multiple Modalities: Fundamentals and Methodologies
Sicheng Zhao, Guoli Jia, Jufeng Yang +2
Humans are emotional creatures. Multiple modalities are often involved when we express emotions, whether we do so explicitly (e.g., facial expression, speech) or implicitly (e.g.,…
Manipulating Identical Filter Redundancy for Efficient Pruning on Deep and Complicated CNN
Xiaohan Ding, Tianxiang Hao, Jungong Han +2
The existence of redundancy in Convolutional Neural Networks (CNNs) enables us to remove some filters/channels with acceptable performance drops. However, the training objective of…
Affective Image Content Analysis: Two Decades Review and New Perspectives
Sicheng Zhao, Xingxu Yao, Jufeng Yang +5
Images can convey rich semantics and induce various emotions in viewers. Recently, with the rapid advancement of emotional intelligence and the explosive growth of visual data, ext…
RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition
Xiaohan Ding, Chunlong Xia, Xiangyu Zhang +3
We propose RepMLP, a multi-layer-perceptron-style neural network building block for image recognition, which is composed of a series of fully-connected (FC) layers. Compared to con…
Diverse Branch Block: Building a Convolution as an Inception-like Unit
Xiaohan Ding, Xiangyu Zhang, Jungong Han +1
We propose a universal building block of Convolutional Neural Network (ConvNet) to improve the performance without any inference-time costs. The block is named Diverse Branch Block…
Computational Emotion Analysis From Images: Recent Advances and Future Directions
Sicheng Zhao, Quanwei Huang, Youbao Tang +4
Emotions are usually evoked in humans by images. Recently, extensive research efforts have been dedicated to understanding the emotions of images. In this chapter, we aim to introd…
RepVGG: Making VGG-style ConvNets Great Again
Xiaohan Ding, Xiangyu Zhang, Ningning Ma +3
We present a simple but powerful architecture of convolutional neural network, which has a VGG-like inference-time body composed of nothing but a stack of 3x3 convolution and ReLU,…