290 citations · 944 across the 42 of their papers we have counts for
12 papers · 1 filter
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…
Information Symmetry Matters: A Modal-Alternating Propagation Network for Few-Shot Learning
Zhong Ji, Zhishen Hou, Xiyao Liu +2
Semantic information provides intra-class consistency and inter-class discriminability beyond visual concepts, which has been employed in Few-Shot Learning (FSL) to achieve further…
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…
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…
Exploring Modality-shared Appearance Features and Modality-invariant Relation Features for Cross-modality Person Re-Identification
Nianchang Huang, Jianan Liu, Qiang Zhang +1
Most existing cross-modality person re-identification works rely on discriminative modality-shared features for reducing cross-modality variations and intra-modality variations. De…
Few-Cost Salient Object Detection with Adversarial-Paced Learning
Dingwen Zhang, Haibin Tian, Jungong Han
Detecting and segmenting salient objects from given image scenes has received great attention in recent years. A fundamental challenge in training the existing deep saliency detect…
Middle-level Fusion for Lightweight RGB-D Salient Object Detection
Nianchang Huang, Qiang Zhang, Jungong Han
Most existing lightweight RGB-D salient object detection (SOD) models are based on two-stream structure or single-stream structure. The former one first uses two sub-networks to ex…
Onfocus Detection: Identifying Individual-Camera Eye Contact from Unconstrained Images
Dingwen Zhang, Bo Wang, Gerong Wang +4
Onfocus detection aims at identifying whether the focus of the individual captured by a camera is on the camera or not. Based on the behavioral research, the focus of an individual…
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…
Densely Nested Top-Down Flows for Salient Object Detection
Chaowei Fang, Haibin Tian, Dingwen Zhang +3
With the goal of identifying pixel-wise salient object regions from each input image, salient object detection (SOD) has been receiving great attention in recent years. One kind of…
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,…