235 citations · 414 across the 25 of their papers we have counts for
8 papers · 1 filter
Video Abnormal Event Detection by Learning to Complete Visual Cloze Tests
Siqi Wang, Guang Yu, Zhiping Cai +3
Although deep neural networks (DNNs) enable great progress in video abnormal event detection (VAD), existing solutions typically suffer from two issues: (1) The localization of vid…
Multi-view Deep One-class Classification: A Systematic Exploration
Siqi Wang, Jiyuan Liu, Guang Yu +5
One-class classification (OCC), which models one single positive class and distinguishes it from the negative class, has been a long-standing topic with pivotal application to real…
Deep Distribution-preserving Incomplete Clustering with Optimal Transport
Mingjie Luo, Siwei Wang, Xinwang Liu +5
Clustering is a fundamental task in the computer vision and machine learning community. Although various methods have been proposed, the performance of existing approaches drops dr…
A Self-Supervised Gait Encoding Approach with Locality-Awareness for 3D Skeleton Based Person Re-Identification
Haocong Rao, Siqi Wang, Xiping Hu +5
Person re-identification (Re-ID) via gait features within 3D skeleton sequences is a newly-emerging topic with several advantages. Existing solutions either rely on hand-crafted de…
Embedded Deep Bilinear Interactive Information and Selective Fusion for Multi-view Learning
Jinglin Xu, Wenbin Li, Jiantao Shen +5
As a concrete application of multi-view learning, multi-view classification improves the traditional classification methods significantly by integrating various views optimally. Al…
Deep Learning for Generic Object Detection: A Survey
Li Liu, Wanli Ouyang, Xiaogang Wang +4
Object detection, one of the most fundamental and challenging problems in computer vision, seeks to locate object instances from a large number of predefined categories in natural…
DeepKSPD: Learning Kernel-matrix-based SPD Representation for Fine-grained Image Recognition
Melih Engin, Lei Wang, Luping Zhou +1
Being symmetric positive-definite (SPD), covariance matrix has traditionally been used to represent a set of local descriptors in visual recognition. Recent study shows that kernel…
A Computational Model of the Short-Cut Rule for 2D Shape Decomposition
Lei Luo, Chunhua Shen, Xinwang Liu +1
We propose a new 2D shape decomposition method based on the short-cut rule. The short-cut rule originates from cognition research, and states that the human visual system prefers t…