31 citations · 63 across the 9 of their papers we have counts for
9 papers
Weakly Supervised Deep Hyperspherical Quantization for Image Retrieval
Jinpeng Wang, Bin Chen, Qiang Zhang +3
Deep quantization methods have shown high efficiency on large-scale image retrieval. However, current models heavily rely on ground-truth information, hindering the application of…
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…
PILC: Practical Image Lossless Compression with an End-to-end GPU Oriented Neural Framework
Ning Kang, Shanzhao Qiu, Shifeng Zhang +2
Generative model based image lossless compression algorithms have seen a great success in improving compression ratio. However, the throughput for most of them is less than 1 MB/s…
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…
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…
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…
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…
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…
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…