Multiple Object Tracking
State-of-the-art leaderboards
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Greatest papers with code
Simple Online and Realtime Tracking with a Deep Association Metric
• nwojke/deep_sort
• 
Simple Online and Realtime Tracking (SORT) is a pragmatic approach to multiple object tracking with a focus on simple, effective algorithms.
LARGE-SCALE PERSON RE-IDENTIFICATION MULTIPLE OBJECT TRACKING
Simple Online and Realtime Tracking
• abewley/sort
•
This paper explores a pragmatic approach to multiple object tracking where the main focus is to associate objects efficiently for online and realtime applications.
Deep Affinity Network for Multiple Object Tracking
• shijieS/SST
• 
In this paper, we harness the power of deep learning for data association in tracking by jointly modelling object appearances and their affinities between different frames in an end-to-end fashion.
Real-Time Multiple Object Tracking - A Study on the Importance of Speed
• samuelmurray/tracking-by-detection
In this project, we implement a multiple object tracker, following the tracking-by-detection paradigm, as an extension of an existing method.
Joint Monocular 3D Vehicle Detection and Tracking
• ucbdrive/3d-vehicle-tracking
•
The framework can not only associate detections of vehicles in motion over time, but also estimate their complete 3D bounding box information from a sequence of 2D images captured on a moving platform.
3D OBJECT DETECTION 3D POSE ESTIMATION AUTONOMOUS VEHICLES MULTIPLE OBJECT TRACKING ONLINE MULTI-OBJECT TRACKING
DeepMOT: A Differentiable Framework for Training Multiple Object Trackers
• yihongXU/deepMOT
•
To directly optimize a tracker based on MOTA and MOTP is difficult, since both the metrics are strongly rely on the Hungarian algorithm, which are non-differentiable.
MOT16: A Benchmark for Multi-Object Tracking
• yihongXU/deepMOT
•
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.
MULTI-OBJECT TRACKING MULTIPLE OBJECT TRACKING MULTIPLE PEOPLE TRACKING
Lucid Data Dreaming for Video Object Segmentation
Our approach is suitable for both single and multiple object segmentation.
MULTIPLE OBJECT TRACKING SEMANTIC SEGMENTATION VIDEO OBJECT SEGMENTATION VIDEO SEMANTIC SEGMENTATION
Multiple Object Tracking with Kernelized Correlation Filters in Urban Mixed Traffic
In this paper, we investigate how a robust visual tracker like KCF can improve multiple object tracking.
Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking
In this work, we present an end-to-end framework to settle data association in online Multiple-Object Tracking (MOT).