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

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Showing 1101–1125 of 1966 papers

TitleStatusHype
3D Multi-Object Tracking with Differentiable Pose Estimation—0
Warped Convolutional Networks: Bridge Homography to sl(3) algebra by Group Convolution—0
Real-time Full-stack Traffic Scene Perception for Autonomous Driving with Roadside Cameras—0
0/1 Deep Neural Networks via Block Coordinate Descent—0
mvHOTA: A multi-view higher order tracking accuracy metric to measure spatial and temporal associations in multi-point detectionCode0
Self-Assessment for Single-Object Tracking in Clutter Using Subjective Logic—0
Object Tracking Using Siamese Network-Based Reinforcement Learning—0
Saccade Mechanisms for Image Classification, Object Detection and Tracking—0
GridShift: A Faster Mode-seeking Algorithm for Image Segmentation and Object Tracking—0
Occlusion-Resistant Instance Segmentation of Piglets in Farrowing Pens Using Center Clustering Network—0
Introduction of a tree-based technique for efficient and real-time label retrieval in the object tracking system—0
Transformers for Multi-Object Tracking on Point Clouds—0
Time3D: End-to-End Joint Monocular 3D Object Detection and Tracking for Autonomous Driving—0
Predictor-corrector algorithms for stochastic optimization under gradual distribution shiftCode0
Recent Advances in Embedding Methods for Multi-Object Tracking: A Survey—0
Towards real-time and energy efficient Siamese tracking -- a hardware-software approach—0
TDT: Teaching Detectors to Track without Fully Annotated Videos—0
CoCoLoT: Combining Complementary Trackers in Long-Term Visual Tracking—0
Category-Independent Articulated Object Tracking with Factor Graphs—0
Multi-Target Active Object Tracking with Monte Carlo Tree Search and Target Motion Modeling—0
Sparse Regularized Correlation Filter for UAV Object Tracking with adaptive Contextual Learning and Keyfilter SelectionCode0
DropTrack -- automatic droplet tracking using deep learning for microfluidic applications—0
A Bayesian Detect to Track System for Robust Visual Object Tracking and Semi-Supervised Model Learning—0
AnimalTrack: A Benchmark for Multi-Animal Tracking in the Wild—0
Single Object Tracking Research: A Survey—0
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All datasetsCOESOTFE108QuadTrackSeaDronesSeeBIRDSAI - ICVGIP 2020KITTIMMPTRACKPerception TestVisEvent

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1HR-CEUTrack-LargeSuccess Rate65—Unverified
2HR-CEUTrack-BaseSuccess Rate63.2—Unverified
3CEUTrack-LargeSuccess Rate62.8—Unverified
4CEUTrack-BaseSuccess Rate62—Unverified
5SiamR-CNNSuccess Rate60.9—Unverified
6TransTSuccess Rate60.5—Unverified
7SuperDiMPSuccess Rate60.2—Unverified
8TrDiMPSuccess Rate60.1—Unverified
9KeepTrackSuccess Rate59.6—Unverified
10AiATrackSuccess Rate59—Unverified
#ModelMetricClaimedVerifiedStatus
1HR-MonTrack-BaseSuccess Rate68.5—Unverified
2HR-MonTrack-TinySuccess Rate66.3—Unverified
3Multi-modalSuccess Rate63.4—Unverified
4PrDiMPSuccess Rate59—Unverified
5DiMPSuccess Rate57.1—Unverified
6MonTrackSuccess Rate54.9—Unverified
7ATOMSuccess Rate46.5—Unverified
8KYSSuccess Rate26.6—Unverified
#ModelMetricClaimedVerifiedStatus
1OmniTrackHOTA23.45—Unverified
2DeepSORTHOTA21.16—Unverified
3OC-SORTHOTA20.83—Unverified
4ByteTrackHOTA20.66—Unverified
5TrackFormerHOTA19.62—Unverified
6HybridSORTHOTA16.64—Unverified
7DiffMOTHOTA16.4—Unverified
8Bot-SORTHOTA15.77—Unverified
#ModelMetricClaimedVerifiedStatus
1DiMP50Success Rate67.33—Unverified
2PrDiMP50Success Rate67—Unverified
3PrDiMP18Success Rate65.9—Unverified
4DiMP18Success Rate64.6—Unverified
5AtomSuccess Rate63.8—Unverified
#ModelMetricClaimedVerifiedStatus
1finalHumans0.14—Unverified
2night_furyHumans0.05—Unverified
3Yolo based methodHumans0.02—Unverified
4finalHumans0—Unverified
#ModelMetricClaimedVerifiedStatus
1M2-Trackmean precision83.4—Unverified
2BATmean precision75.2—Unverified
#ModelMetricClaimedVerifiedStatus
1UMMT3DMOTA95—Unverified
2MMPTRACK3DMOTA94.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Siam-FCAverage IOU0.66—Unverified
#ModelMetricClaimedVerifiedStatus
1RT-MDNetPrecision Plot0.63—Unverified