SOTAVerified

Multiple Object Tracking

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.

Source: SOT for MOT

Papers

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Showing 101–150 of 318 papers

TitleStatusHype
When to Extract ReID Features: A Selective Approach for Improved Multiple Object TrackingCode1
Making Higher Order MOT Scalable: An Efficient Approximate Solver for Lifted Disjoint PathsCode1
Multi-Object Tracking and Segmentation via Neural Message PassingCode1
Prototypical Cross-Attention Networks for Multiple Object Tracking and SegmentationCode1
SparseTrack: Multi-Object Tracking by Performing Scene Decomposition based on Pseudo-DepthCode1
Heterogeneous Graph Transformer for Multiple Tiny Object Tracking in RGB-T VideosCode1
History-Aware Transformation of ReID Features for Multiple Object TrackingCode1
TransTrack: Multiple Object Tracking with TransformerCode1
DEFT: Detection Embeddings for TrackingCode1
Joint Graph Decomposition & Node Labeling: Problem, Algorithms, Applications—0
Does Video Compression Impact Tracking Accuracy?—0
An Improved End-to-End Multi-Target Tracking Method Based on Transformer Self-Attention—0
Bayesian nonparametric modeling for predicting dynamic dependencies in multiple object tracking—0
MOTS: Multiple Object Tracking for General Categories Based On Few-Shot Method—0
DecoderTracker: Decoder-Only Method for Multiple-Object Tracking—0
Intelligent Intersection: Two-Stream Convolutional Networks for Real-time Near Accident Detection in Traffic Video—0
INTACT: Inducing Noise Tolerance through Adversarial Curriculum Training for LiDAR-based Safety-Critical Perception and Autonomy—0
Depth Perspective-aware Multiple Object Tracking—0
Detection- and Trajectory-Level Exclusion in Multiple Object Tracking—0
Interactive Multi-scale Fusion of 2D and 3D Features for Multi-object Tracking—0
DiffMOT: A Real-time Diffusion-based Multiple Object Tracker with Non-linear Prediction—0
Is Multiple Object Tracking a Matter of Specialization?—0
Instance Flow Based Online Multiple Object Tracking—0
Inference for multiple object tracking: A Bayesian nonparametric approach—0
Dense Scene Multiple Object Tracking with Box-Plane Matching—0
BaboonLand Dataset: Tracking Primates in the Wild and Automating Behaviour Recognition from Drone Videos—0
DeNoising-MOT: Towards Multiple Object Tracking with Severe Occlusions—0
Improving tracking with a tracklet associator—0
Automatic tracking of protein vesicles—0
Deep Similarity Metric Learning for Real-Time Pedestrian Tracking—0
Improving Multiple Object Tracking With Single Object Tracking—0
Accurate Object Association and Pose Updating for Semantic SLAM—0
3D Multiple Object Tracking on Autonomous Driving: A Literature Review—0
MTMMC: A Large-Scale Real-World Multi-Modal Camera Tracking Benchmark—0
Improving Multiple Object Tracking with Optical Flow and Edge Preprocessing—0
IA-MOT: Instance-Aware Multi-Object Tracking with Motion Consistency—0
Automatic individual pig detection and tracking in surveillance videos—0
A Large Scale Urban Surveillance Video Dataset for Multiple-Object Tracking and Behavior Analysis—0
Deep Learning in Video Multi-Object Tracking: A Survey—0
Handling Heavy Occlusion in Dense Crowd Tracking by Focusing on the Heads—0
Deep HM-SORT: Enhancing Multi-Object Tracking in Sports with Deep Features, Harmonic Mean, and Expansion IOU—0
Automated Surgical Skill Assessment in Endoscopic Pituitary Surgery using Real-time Instrument Tracking on a High-fidelity Bench-top Phantom—0
MOTSLAM: MOT-assisted monocular dynamic SLAM using single-view depth estimation—0
GSLAMOT: A Tracklet and Query Graph-based Simultaneous Locating, Mapping, and Multiple Object Tracking System—0
A Joint Intensity-Neuromorphic Event Imaging System for Resource Constrained Devices—0
MotionTrack: Learning Motion Predictor for Multiple Object Tracking—0
GMMCP Tracker: Globally Optimal Generalized Maximum Multi Clique Problem for Multiple Object Tracking—0
Automated learning with a probabilistic programming language: Birch—0
Generalizing Multiple Object Tracking to Unseen Domains by Introducing Natural Language Representation—0
CVPR19 Tracking and Detection Challenge: How crowded can it get?—0
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All datasetsKITTI Test (Online Methods)BDD100K valBDD100K testCroHDSportsMOTKITTI Test (Offline Methods)RADIATEWaymo Open DatasetGMOT-40UA-DETRACYouTube-Hands

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SRK ODESAMOTA90.03—Unverified
2MOSTFusionMOTA84.83—Unverified
3mmMOT-normalMOTA84.77—Unverified
43DTMOTA84.52—Unverified
5Mono3DTMOTA84.52—Unverified
6RRC-IIITHMOTA84.24—Unverified
7RobMOT (Dynamic)HOTA81.8—Unverified
8RobMOTHOTA81.76—Unverified
9MCTrackHOTA81.07—Unverified
10KFDLHOTA81.06—Unverified
#ModelMetricClaimedVerifiedStatus
1ByteTrackmMOTA45.5—Unverified
2UNINEXT-HmMOTA44.2—Unverified
3MOTRv2mMOTA43.6—Unverified
4QDTrackmMOTA42.1—Unverified
5ContrasTRmMOTA41.7—Unverified
6UnicornmMOTA41.2—Unverified
7TETermMOTA39.1—Unverified
8QDTrackmMOTA36.6—Unverified
9Adaptive-searching -windows TrackermMOTA34.4—Unverified
#ModelMetricClaimedVerifiedStatus
1ContrasTRmMOTA42.8—Unverified
2SUSHImMOTA40.2—Unverified
3ByteTrackmMOTA40.1—Unverified
4QDtrackmMOTA35.6—Unverified
5Yu et al.mMOTA26.3—Unverified
#ModelMetricClaimedVerifiedStatus
1PP-TrackingMOTA72.6—Unverified
2OC-SORTMOTA67.9—Unverified
3HeadHunter-TMOTA63.6—Unverified
4TracktorMOTA58.9—Unverified
5SORTMOTA46.4—Unverified
#ModelMetricClaimedVerifiedStatus
1MOTIP (Deformable DETR, with SportsMOT val)HOTA75.2—Unverified
2TrackSSMHOTA74.4—Unverified
3MOTIP (Deformable DETR)HOTA71.9—Unverified
#ModelMetricClaimedVerifiedStatus
1MCTrackHOTA82.75—Unverified
2BiTrackHOTA82.7—Unverified
#ModelMetricClaimedVerifiedStatus
1SIRAMOTA47.79—Unverified
2TempoRadarMOTA37.91—Unverified
#ModelMetricClaimedVerifiedStatus
1QDTrackMOTA55.6—Unverified
2RetinaTrackMOTA44.92—Unverified
#ModelMetricClaimedVerifiedStatus
1MAC-SORTHOTA58.58—Unverified
#ModelMetricClaimedVerifiedStatus
1EB & TADNMOTA23.7—Unverified
#ModelMetricClaimedVerifiedStatus
1HandLerMOTA70—Unverified