activity
20192022
most citedMaintaining Discrimination and Fairness in Class Incremental Learning

31 citations · 36 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV20222 cited

Contrastive Masked Autoencoders for Self-Supervised Video Hashing

Yuting Wang, Jinpeng Wang, Bin Chen +2

Self-Supervised Video Hashing (SSVH) models learn to generate short binary representations for videos without ground-truth supervision, facilitating large-scale video retrieval eff…

cs.LG2021

Learnable Hypergraph Laplacian for Hypergraph Learning

Jiying Zhang, Yuzhao Chen, Xi Xiao +2

HyperGraph Convolutional Neural Networks (HGCNNs) have demonstrated their potential in modeling high-order relations preserved in graph structured data. However, most existing conv…

cs.CV20202 cited

Adversarial Attack on Deep Product Quantization Network for Image Retrieval

Yan Feng, Bin Chen, Tao Dai +1

Deep product quantization network (DPQN) has recently received much attention in fast image retrieval tasks due to its efficiency of encoding high-dimensional visual features espec…

cs.CV201931 cited

Maintaining Discrimination and Fairness in Class Incremental Learning

Bowen Zhao, Xi Xiao, Guojun Gan +2

Deep neural networks (DNNs) have been applied in class incremental learning, which aims to solve common real-world problems of learning new classes continually. One drawback of sta…

cs.MM2019

AdaCompress: Adaptive Compression for Online Computer Vision Services

Hongshan Li, Yu Guo, Zhi Wang +2

With the growth of computer vision based applications and services, an explosive amount of images have been uploaded to cloud servers which host such computer vision algorithms, us…

cs.LG20191 cited

Self-Paced Probabilistic Principal Component Analysis for Data with Outliers

Bowen Zhao, Xi Xiao, Wanpeng Zhang +2

Principal Component Analysis (PCA) is a popular tool for dimensionality reduction and feature extraction in data analysis. There is a probabilistic version of PCA, known as Probabi…