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Found 12 papers, 4 papers with code
From Synthetic to Real: Unveiling the Power of Synthetic Data for Video Person Re-ID
In this paper, we study a new problem of cross-domain video based person re-identification (Re-ID).
Unveiling the Power of Self-supervision for Multi-view Multi-human Association and Tracking
Multi-view multi-human association and tracking (MvMHAT), is a new but important problem for multi-person scene video surveillance, aiming to track a group of people over time in each view, as well as to identify the same person across different views at the same time, which is different from previous MOT and multi-camera MOT tasks only considering the over-time human tracking.
From a Bird's Eye View to See: Joint Camera and Subject Registration without the Camera Calibration
We tackle a new problem of multi-view camera and subject registration in the bird's eye view (BEV) without pre-given camera calibration.
A Benchmark of Video-Based Clothes-Changing Person Re-Identification
In this paper, we focus on the relatively new yet practical problem of clothes-changing video-based person re-identification (CCVReID), which is less studied.
From Indoor To Outdoor: Unsupervised Domain Adaptive Gait Recognition
In this paper, we study a new problem of unsupervised domain adaptive gait recognition (UDA-GR), that learns a gait identifier with supervised labels from the indoor scenes (source domain), and is applied to the outdoor wild scenes (target domain).
Access Trends of In-network Cache for Scientific Data
Our study shows that this distributed storage cache is able to reduce the network traffic volume by a factor of 2. 35 during a part of the study period.
Single Object Tracking Research: A Survey
Visual object tracking is an important task in computer vision, which has many real-world applications, e. g., video surveillance, visual navigation.
Self-supervised Social Relation Representation for Human Group Detection
The core of human group detection is the human social relation representation and division. In this paper, we propose a new two-stage multi-head framework for human group detection.
Panoramic Human Activity Recognition
To obtain a more comprehensive activity understanding for a crowded scene, in this paper, we propose a new problem of panoramic human activity recognition (PAR), which aims to simultaneous achieve the individual action, social group activity, and global activity recognition.
Combining the Silhouette and Skeleton Data for Gait Recognition
Gait recognition, a long-distance biometric technology, has aroused intense interest recently.
Connecting the Complementary-View Videos: Joint Camera Identification and Subject Association
In this paper, we develop a new approach that can simultaneously handle three tasks: i) localizing the side-view camera in the top view; ii) estimating the view direction of the side-view camera; iii) detecting and associating the same subjects on the ground across the complementary views.
Multiple Human Association between Top and Horizontal Views by Matching Subjects' Spatial Distributions
However, for such collaborative analysis, the first step is to associate people, referred to as subjects in this paper, across these two views.
