Chained-Tracker: Chaining Paired Attentive Regression Results for End-to-End Joint Multiple-Object Detection and Tracking

07/29/2020
by   Jinlong Peng, et al.
6

Existing Multiple-Object Tracking (MOT) methods either follow the tracking-by-detection paradigm to conduct object detection, feature extraction and data association separately, or have two of the three subtasks integrated to form a partially end-to-end solution. Going beyond these sub-optimal frameworks, we propose a simple online model named Chained-Tracker (CTracker), which naturally integrates all the three subtasks into an end-to-end solution (the first as far as we know). It chains paired bounding boxes regression results estimated from overlapping nodes, of which each node covers two adjacent frames. The paired regression is made attentive by object-attention (brought by a detection module) and identity-attention (ensured by an ID verification module). The two major novelties: chained structure and paired attentive regression, make CTracker simple, fast and effective, setting new MOTA records on MOT16 and MOT17 challenge datasets (67.6 and 66.6, respectively), without relying on any extra training data. The source code of CTracker can be found at: github.com/pjl1995/CTracker.

READ FULL TEXT

page 5

page 12

page 20

research
03/23/2021

Global Correlation Network: End-to-End Joint Multi-Object Detection and Tracking

Multi-object tracking (MOT) has made great progress in recent years, but...
research
07/13/2020

End-to-End Multi-Object Tracking with Global Response Map

Most existing Multi-Object Tracking (MOT) approaches follow the Tracking...
research
09/10/2018

Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers

Online Multi-Object Tracking (MOT) from videos is a challenging computer...
research
08/19/2023

DiffusionTrack: Diffusion Model For Multi-Object Tracking

Multi-object tracking (MOT) is a challenging vision task that aims to de...
research
01/05/2022

Improving Object Detection, Multi-object Tracking, and Re-Identification for Disaster Response Drones

We aim to detect and identify multiple objects using multiple cameras an...
research
03/30/2022

TR-MOT: Multi-Object Tracking by Reference

Multi-object Tracking (MOT) generally can be split into two sub-tasks, i...
research
07/08/2019

A unified neural network for object detection, multiple object tracking and vehicle re-identification

Deep SORTwojke2017simple is a tracking-by-detetion approach to multiple ...

Please sign up or login with your details

Forgot password? Click here to reset