SOTAVerified

Object Tracking

Object tracking is the task of taking an initial set of object detections, creating a unique ID for each of the initial detections, and then tracking each of the objects as they move around frames in a video, maintaining the ID assignment. State-of-the-art methods involve fusing data from RGB and event-based cameras to produce more reliable object tracking. CNN-based models using only RGB images as input are also effective. The most popular benchmark is OTB. There are several evaluation metrics specific to object tracking, including HOTA, MOTA, IDF1, and Track-mAP.

( Image credit: Towards-Realtime-MOT )

Papers

Showing 13011350 of 1966 papers

TitleStatusHype
Multi-Object Tracking using Poisson Multi-Bernoulli Mixture Filtering for Autonomous Vehicles0
Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping0
Learning Irreducible Representations of Noncommutative Lie Groups0
Optimized Object Tracking Technique Using Kalman Filter0
Efficient data-driven encoding of scene motion using Eccentricity0
Multiple Convolutional Features in Siamese Networks for Object TrackingCode0
The SpaceNet Multi-Temporal Urban Development Challenge0
Phase Space Reconstruction Network for Lane Intrusion Action Recognition0
The Multi-Temporal Urban Development SpaceNet DatasetCode0
MOTS R-CNN: Cosine-margin-triplet loss for multi-object tracking0
Revisiting the details when evaluating a visual trackerCode0
COLLIDE-PRED: Prediction of On-Road Collision From Surveillance Videos0
A two-stage data association approach for 3D Multi-object Tracking0
Semi-Automatic Annotation For Visual Object TrackingCode0
TrackMPNN: A Message Passing Graph Neural Architecture for Multi-Object Tracking0
Multi-object Tracking with a Hierarchical Single-branch Network0
TGCN: Time Domain Graph Convolutional Network for Multiple Objects TrackingCode0
Weakly Supervised Multi-Object Tracking and Segmentation0
EMPIRICAL UPPER BOUND IN OBJECT DETECTION0
A General Recurrent Tracking Framework Without Real Data0
Beyond the Pixels: Exploring the Effects of Bit-Level Network and File Corruptions on Video Model Robustness0
Temporally-Transferable Perturbations: Efficient, One-Shot Adversarial Attacks for Online Visual Object Trackers0
GAKP: GRU Association and Kalman Prediction for Multiple Object Tracking0
Coarse-to-Fine Object Tracking Using Deep Features and Correlation FiltersCode0
Limitation of Acyclic Oriented Graphs Matching as Cell Tracking Accuracy Measure when Evaluating Mitosis0
Accurate Object Association and Pose Updating for Semantic SLAM0
Computer Vision based Animal Collision Avoidance Framework for Autonomous Vehicles0
Recent Advances of Generic Object Detection with Deep Learning: A Review0
End-to-end Deep Object Tracking with Circular Loss Function for Rotated Bounding Box0
Seeing Behind Objects for 3D Multi-Object Tracking in RGB-D Sequences0
FlowMOT: 3D Multi-Object Tracking by Scene Flow Association0
AutoSelect: Automatic and Dynamic Detection Selection for 3D Multi-Object Tracking0
Learning Tactile Models for Factor Graph-based Estimation0
Isometric Multi-Shape Matching0
Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking0
Generalised Bayesian Filtering via Sequential Monte Carlo0
A CRF-based Framework for Tracklet Inactivation in Online Multi-Object Tracking0
A Hypergradient Approach to Robust Regression without Correspondence0
SFTrack++: A Fast Learnable Spectral Segmentation Approach for Space-Time Consistent TrackingCode0
A Deep Learning Bidirectional Temporal Tracking Algorithm for Automated Blood Cell Counting from Non-invasive Capillaroscopy VideosCode0
Relation3DMOT: Exploiting Deep Affinity for 3D Multi-Object Tracking from View Aggregation0
Is First Person Vision Challenging for Object Tracking?0
An Occlusion‐aware Edge‐Based Method for Monocular 3D Object Tracking using Edge Confidence.Code0
Graph Attention Tracking0
Siamese Tracking with Lingual Object ConstraintsCode0
Transparent Object Tracking Benchmark0
Learning Local Feature Descriptors for Multiple Object Tracking0
Online Multi-Object Tracking with delta-GLMB Filter based on Occlusion and Identity Switch Handling0
TRAT: Tracking by Attention Using Spatio-Temporal Features0
Efficient Data Association and Uncertainty Quantification for Multi-Object Tracking0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HR-CEUTrack-LargeSuccess Rate65Unverified
2HR-CEUTrack-BaseSuccess Rate63.2Unverified
3CEUTrack-LargeSuccess Rate62.8Unverified
4CEUTrack-BaseSuccess Rate62Unverified
5SiamR-CNNSuccess Rate60.9Unverified
6TransTSuccess Rate60.5Unverified
7SuperDiMPSuccess Rate60.2Unverified
8TrDiMPSuccess Rate60.1Unverified
9KeepTrackSuccess Rate59.6Unverified
10AiATrackSuccess Rate59Unverified
#ModelMetricClaimedVerifiedStatus
1HR-MonTrack-BaseSuccess Rate68.5Unverified
2HR-MonTrack-TinySuccess Rate66.3Unverified
3Multi-modalSuccess Rate63.4Unverified
4PrDiMPSuccess Rate59Unverified
5DiMPSuccess Rate57.1Unverified
6MonTrackSuccess Rate54.9Unverified
7ATOMSuccess Rate46.5Unverified
8KYSSuccess Rate26.6Unverified
#ModelMetricClaimedVerifiedStatus
1OmniTrackHOTA23.45Unverified
2DeepSORTHOTA21.16Unverified
3OC-SORTHOTA20.83Unverified
4ByteTrackHOTA20.66Unverified
5TrackFormerHOTA19.62Unverified
6HybridSORTHOTA16.64Unverified
7DiffMOTHOTA16.4Unverified
8Bot-SORTHOTA15.77Unverified
#ModelMetricClaimedVerifiedStatus
1DiMP50Success Rate67.33Unverified
2PrDiMP50Success Rate67Unverified
3PrDiMP18Success Rate65.9Unverified
4DiMP18Success Rate64.6Unverified
5AtomSuccess Rate63.8Unverified
#ModelMetricClaimedVerifiedStatus
1finalHumans0.14Unverified
2night_furyHumans0.05Unverified
3Yolo based methodHumans0.02Unverified
4finalHumans0Unverified
#ModelMetricClaimedVerifiedStatus
1M2-Trackmean precision83.4Unverified
2BATmean precision75.2Unverified
#ModelMetricClaimedVerifiedStatus
1UMMT3DMOTA95Unverified
2MMPTRACK3DMOTA94.8Unverified
#ModelMetricClaimedVerifiedStatus
1Siam-FCAverage IOU0.66Unverified
#ModelMetricClaimedVerifiedStatus
1RT-MDNetPrecision Plot0.63Unverified