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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1551–1600 of 1966 papers

TitleStatusHype
UnsMOT: Unified Framework for Unsupervised Multi-Object Tracking with Geometric Topology Guidance—0
Unsupervised Green Object Tracker (GOT) without Offline Pre-training—0
Unsupervised learning-based long-term superpixel tracking—0
Unsupervised Learning of Object Structure and Dynamics from Videos—0
Unsupervised Lightweight Single Object Tracking with UHP-SOT++—0
Unsupervised Multiple-Object Tracking with a Dynamical Variational Autoencoder—0
Unsupervised Multiple Person Tracking using AutoEncoder-Based Lifted Multicuts—0
Unsupervised Video Object Segmentation with Joint Hotspot Tracking—0
Unveiling the Power of Deep Tracking—0
Using Cross-Domain Detection Loss to Infer Multi-Scale Information for Improved Tiny Head Tracking—0
USVTrack: USV-Based 4D Radar-Camera Tracking Dataset for Autonomous Driving in Inland Waterways—0
UTM: A Unified Multiple Object Tracking Model With Identity-Aware Feature Enhancement—0
UTOPIA: Unconstrained Tracking Objects without Preliminary Examination via Cross-Domain Adaptation—0
VariabilityTrack:Multi-Object Tracking with Variable Speed Object Movement—0
Variance Reduction for Reinforcement Learning in Input-Driven Environments—0
Variational Bayes for robust radar single object tracking—0
Vehicle Detection and Tracking From Surveillance Cameras in Urban Scenes—0
Vessel Re-identification and Activity Detection in Thermal Domain for Maritime Surveillance—0
VETRA: A Dataset for Vehicle Tracking in Aerial Imagery - New Challenges for Multi-Object Tracking—0
V-HOP: Visuo-Haptic 6D Object Pose Tracking—0
Video Object Segmentation and Tracking: A Survey—0
Video Object Segmentation using Tracked Object Proposals—0
Video object tracking based on YOLOv7 and DeepSORT—0
Video Processing from Electro-optical Sensors for Object Detection and Tracking in Maritime Environment: A Survey—0
VideoSAM: Open-World Video Segmentation—0
Video Tracking Using Learned Hierarchical Features—0
View-Centric Multi-Object Tracking with Homographic Matching in Moving UAV—0
Virtual Worlds as Proxy for Multi-Object Tracking Analysis—0
Vision Meets Drones: A Challenge—0
Visions of a generalized probability theory—0
Visual Explanation by High-Level Abduction: On Answer-Set Programming Driven Reasoning about Moving Objects—0
Visual-Inertial Telepresence for Aerial Manipulation—0
Visual Localization via Semantic Structures in Autonomous Photovoltaic Power Plant Inspection—0
Visual Multiple-Object Tracking for Unknown Clutter Rate—0
Visual Object Tracking across Diverse Data Modalities: A Review—0
Visual Object Tracking based on Adaptive Siamese and Motion Estimation Network—0
Visual Object Tracking by Segmentation with Graph Convolutional Network—0
Visual Object Tracking in First Person Vision—0
Visual Object Tracking on Multi-modal RGB-D Videos: A Review—0
Visual object tracking performance measures revisited—0
Visual Object Tracking with Discriminative Filters and Siamese Networks: A Survey and Outlook—0
Visual SLAMMOT Considering Multiple Motion Models—0
Visual Tracking via Dynamic Graph Learning—0
Visual Tracking via Nonnegative Regularization Multiple Locality Coding—0
Visual Tracking With Fully Convolutional Networks—0
VOVTrack: Exploring the Potentiality in Videos for Open-Vocabulary Object Tracking—0
VR-based generation of photorealistic synthetic data for training hand-object tracking models—0
Walker: Self-supervised Multiple Object Tracking by Walking on Temporal Appearance Graphs—0
Walking = Traversable? : Traversability Prediction via Multiple Human Object Tracking under Occlusion—0
Warped Convolutional Networks: Bridge Homography to sl(3) algebra by Group Convolution—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