Multiple Object Tracking
Leaderboards
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
|---|---|---|---|---|---|---|
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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.
Towards Real-Time Multi-Object Tracking
• Zhongdao/Towards-Realtime-MOT
• 
In this paper, we propose an MOT system that allows target detection and appearance embedding to be learned in a shared model.
SOTA for Multi-Object Tracking on MOT16 (using extra training data)
MULTI-OBJECT TRACKING MULTIPLE OBJECT TRACKING MULTI-TASK LEARNING
Joint Monocular 3D Vehicle Detection and Tracking
ICCV 2019
• 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 TRAJECTORY PREDICTION
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.
How To Train Your Deep Multi-Object Tracker
• yihongXU/deepMOT
•
In this paper, we bridge this gap by proposing a differentiable proxy of MOTA and MOTP, which we combine in a loss function suitable for end-to-end training of deep multi-object trackers.
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
Real-Time Multiple Object Tracking - A Study on the Importance of Speed
In this project, we implement a multiple object tracker, following the tracking-by-detection paradigm, as an extension of an existing method.
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
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).