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 1001–1050 of 1966 papers

TitleStatusHype
CIRI: Curricular Inactivation for Residue-aware One-shot Video InpaintingCode0
F&F Attack: Adversarial Attack against Multiple Object Trackers by Inducing False Negatives and False Positives—0
Deep Active Contours for Real-time 6-DoF Object Tracking—0
Heterogeneous Diversity Driven Active Learning for Multi-Object Tracking—0
UTM: A Unified Multiple Object Tracking Model With Identity-Aware Feature Enhancement—0
End-to-end 3D Tracking with Decoupled Queries—0
Multiple Planar Object Tracking—0
Tracking without Label: Unsupervised Multiple Object Tracking via Contrastive Similarity Learning—0
Tracking Passengers and Baggage Items using Multiple Overhead Cameras at Security CheckpointsCode0
High-temporal-resolution event-based vehicle detection and tracking—0
Beyond SOT: Tracking Multiple Generic Objects at Once—0
Tracking by Associating Clips—0
Detection-aware multi-object tracking evaluationCode0
Neural Enhanced Belief Propagation for Multiobject TrackingCode0
Learning a Fast 3D Spectral Approach to Object Segmentation and Tracking over Space and Time—0
Event-based Visual Tracking in Dynamic EnvironmentsCode0
Joint Counting, Detection and Re-Identification for Multi-Object Tracking—0
Sparse Message Passing Network with Feature Integration for Online Multiple Object Tracking—0
Generalizing Multiple Object Tracking to Unseen Domains by Introducing Natural Language Representation—0
On Designing Light-Weight Object Trackers through Network Pruning: Use CNNs or Transformers?Code0
1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results—0
Improving Siamese Based Trackers with Light or No Training through Multiple Templates and Temporal Network—0
β-Multivariational Autoencoder for Entangled Representation Learning in Video FramesCode0
Unifying Tracking and Image-Video Object Detection—0
Multi-Camera Multi-Object Tracking on the Move via Single-Stage Global Association Approach—0
Robust Online Video Instance Segmentation with Track QueriesCode0
Semantic keypoint extraction for scanned animals using multi-depth-camera systemsCode0
3D-SiamMask: Vision-Based Multi-Rotor Aerial-Vehicle Tracking for a Moving ObjectCode0
CXTrack: Improving 3D Point Cloud Tracking with Contextual Information—0
Partial Binarization of Neural Networks for Budget-Aware Efficient Learning—0
An Improved End-to-End Multi-Target Tracking Method Based on Transformer Self-Attention—0
Efficient Joint Detection and Multiple Object Tracking with Spatially Aware Transformer—0
ShaSTA: Modeling Shape and Spatio-Temporal Affinities for 3D Multi-Object Tracking—0
Estimation of Appearance and Occupancy Information in Birds Eye View from Surround Monocular Images—0
Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report—0
A Deep-Unfolded Spatiotemporal RPCA Network For L+S Decomposition—0
Learning Dual-Fused Modality-Aware Representations for RGBD Tracking—0
Development and evaluation of automated localisation and reconstruction of all fruits on tomato plants in a greenhouse based on multi-view perception and 3D multi-object tracking—0
TripletTrack: 3D Object Tracking using Triplet Embeddings and LSTM—0
End-to-end Tracking with a Multi-query Transformer—0
A Flexible-Frame-Rate Vision-Aided Inertial Object Tracking System for Mobile Devices—0
A Complete Recipe for Bayesian Knowledge Transfer: Object Tracking—0
Cell tracking for live-cell microscopy using an activity-prioritized assignment strategyCode0
RLM-Tracking: Online Multi-Pedestrian Tracking Supported by Relative Location Mapping—0
RT-MOT: Confidence-Aware Real-Time Scheduling Framework for Multi-Object Tracking Tasks—0
Track Targets by Dense Spatio-Temporal Position Encoding—0
AttTrack: Online Deep Attention Transfer for Multi-object Tracking—0
Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices—0
OST: Efficient One-stream Network for 3D Single Object Tracking in Point Clouds—0
Instance Segmentation with Cross-Modal Consistency—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