Multi-Object Tracking

116 papers with code • 11 benchmarks • 18 datasets

Multiple Object Tracking is the problem of automatically identifying multiple objects in a video and representing them as a set of trajectories with high accuracy.

Libraries

Use these libraries to find Multi-Object Tracking models and implementations

Most implemented papers

Simple Online and Realtime Tracking

abewley/sort 2 Feb 2016

This paper explores a pragmatic approach to multiple object tracking where the main focus is to associate objects efficiently for online and realtime applications.

FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking

ifzhang/FairMOT 4 Apr 2020

Formulating MOT as multi-task learning of object detection and re-ID in a single network is appealing since it allows joint optimization of the two tasks and enjoys high computation efficiency.

Towards Real-Time Multi-Object Tracking

Zhongdao/Towards-Realtime-MOT ECCV 2020

In this paper, we propose an MOT system that allows target detection and appearance embedding to be learned in a shared model.

Tracking without bells and whistles

phil-bergmann/tracking_wo_bnw ICCV 2019

Therefore, we motivate our approach as a new tracking paradigm and point out promising future research directions.

MOT16: A Benchmark for Multi-Object Tracking

PaddlePaddle/PaddleDetection 2 Mar 2016

Recently, a new benchmark for Multiple Object Tracking, MOTChallenge, was launched with the goal of collecting existing and new data and creating a framework for the standardized evaluation of multiple object tracking methods.

ByteTrack: Multi-Object Tracking by Associating Every Detection Box

ifzhang/ByteTrack arXiv 2021

ByteTrack also achieves state-of-the-art performance on MOT20, HiEve and BDD100K tracking benchmarks.

Tracking Objects as Points

xingyizhou/CenterTrack ECCV 2020

Nowadays, tracking is dominated by pipelines that perform object detection followed by temporal association, also known as tracking-by-detection.

Rethinking the competition between detection and ReID in Multi-Object Tracking

JudasDie/SOTS 23 Oct 2020

However, the inherent differences and relations between detection and re-identification (ReID) are unconsciously overlooked because of treating them as two isolated tasks in the one-shot tracking paradigm.

TraSw: Tracklet-Switch Adversarial Attacks against Multi-Object Tracking

derryhub/fairmot-attack 17 Nov 2021

To our knowledge, this is the first work on the adversarial attack against pedestrian MOT trackers.

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

mlvlab/drone_ai_challenge 5 Jan 2022

In the second approach, although DeepSORT only processes a quarter of all frames due to hardware and time limitations, our model with DeepSORT (42. 9%) outperforms FairMOT (71. 4%) in terms of recall.