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Found 8 papers, 4 papers with code
Real-time Multiple People Tracking with Deeply Learned Candidate Selection and Person Re-Identification
Online multi-object tracking is a fundamental problem in time-critical video analysis applications.
Ranked #4 on
Online Multi-Object Tracking
on MOT16
Large-Scale Person Re-Identification
Multi-Object Tracking
+2
Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS
To further verify the scalability of our method, we propose a new large-scale multi-human dataset with 12 to 28 camera views.
Ranked #9 on
3D Multi-Person Pose Estimation
on Campus
Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch Normalization
The fundamental difficulty in person re-identification (ReID) lies in learning the correspondence among individual cameras.
Ranked #16 on
Unsupervised Domain Adaptation
on Duke to Market
Direct Transfer Person Re-identification
Domain Adaptive Person Re-Identification
+2
UnrealPerson: An Adaptive Pipeline towards Costless Person Re-identification
The main difficulty of person re-identification (ReID) lies in collecting annotated data and transferring the model across different domains.
Cross-Resolution Person Re-identification with Deep Antithetical Learning
One paradigm to deal with this problem is to use some complicated methods for mapping all images into an artificial image space, which however will disrupt the natural image distribution and requires heavy image preprocessing.
Learning Lightweight Pedestrian Detector with Hierarchical Knowledge Distillation
It remains very challenging to build a pedestrian detection system for real world applications, which demand for both accuracy and speed.
Multi-Task Learning via Co-Attentive Sharing for Pedestrian Attribute Recognition
In this paper, we propose a novel Co-Attentive Sharing (CAS) module which extracts discriminative channels and spatial regions for more effective feature sharing in multi-task learning.
Spatiotemporal Transformer for Video-based Person Re-identification
Recently, the Transformer module has been transplanted from natural language processing to computer vision.
