activity
20172021
most citedBIT: Biologically Inspired Tracker

47 citations · 83 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV20211 cited

UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning

Zhigang Dai, Bolun Cai, Yugeng Lin +1

Momentum Contrast (MoCo) achieves great success for unsupervised visual representation. However, there are a lot of supervised and semi-supervised datasets, which are already label…

cs.CV2019

Listwise View Ranking for Image Cropping

Weirui Lu, Xiaofen Xing, Bolun Cai +1

Rank-based Learning with deep neural network has been widely used for image cropping. However, the performance of ranking-based methods is often poor and this is mainly due to two…

cs.CV201947 cited

BIT: Biologically Inspired Tracker

Bolun Cai, Xiangmin Xu, Xiaofen Xing +3

Visual tracking is challenging due to image variations caused by various factors, such as object deformation, scale change, illumination change and occlusion. Given the superior tr…

cs.CV20177 cited

FReLU: Flexible Rectified Linear Units for Improving Convolutional Neural Networks

Suo Qiu, Xiangmin Xu, Bolun Cai

Rectified linear unit (ReLU) is a widely used activation function for deep convolutional neural networks. However, because of the zero-hard rectification, ReLU networks miss the be…

cs.CV20176 cited

Single Image Super-Resolution Using Multi-Scale Convolutional Neural Network

Xiaoyi Jia, Xiangmin Xu, Bolun Cai +1

Methods based on convolutional neural network (CNN) have demonstrated tremendous improvements on single image super-resolution. However, the previous methods mainly restore images…

cs.CV201722 cited

Multi-scale Convolutional Neural Networks for Crowd Counting

Lingke Zeng, Xiangmin Xu, Bolun Cai +2

Crowd counting on static images is a challenging problem due to scale variations. Recently deep neural networks have been shown to be effective in this task. However, existing neur…