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 1701–1750 of 1966 papers

TitleStatusHype
Incremental discriminative color object tracking—0
In Defense and Revival of Bayesian Filtering for Thermal Infrared Object Tracking—0
In Defense of Clip-based Video Relation Detection—0
In Defense of Color-Based Model-Free Tracking—0
Inference for multiple object tracking: A Bayesian nonparametric approach—0
Infinite Latent Feature Selection: A Probabilistic Latent Graph-Based Ranking Approach—0
InfraredTags: Embedding Invisible AR Markers and Barcodes Using Low-Cost, Infrared-Based 3D Printing and Imaging Tools—0
Innovative Texture Database Collecting Approach and Feature Extraction Method based on Combination of Gray Tone Difference Matrixes, Local Binary Patterns,and K-means Clustering—0
Inserting Videos into Videos—0
Instance Flow Based Online Multiple Object Tracking—0
Instance-Level Future Motion Estimation in a Single Image Based on Ordinal Regression—0
Instance-Level Video Segmentation From Object Tracks—0
Instance Segmentation with Cross-Modal Consistency—0
Instant 3D Object Tracking with Applications in Augmented Reality—0
Instant-NVR: Instant Neural Volumetric Rendering for Human-object Interactions from Monocular RGBD Stream—0
INTACT: Inducing Noise Tolerance through Adversarial Curriculum Training for LiDAR-based Safety-Critical Perception and Autonomy—0
Integrating Efficient Optimal Transport and Functional Maps For Unsupervised Shape Correspondence Learning—0
Integration of the 3D Environment for UAV Onboard Visual Object Tracking—0
Integration of Regularized l1 Tracking and Instance Segmentation for Video Object Tracking—0
Intelligent driving vehicle front multi-target tracking and detection based on YOLOv5 and point cloud 3D projection—0
Intelligent Intersection: Two-Stream Convolutional Networks for Real-time Near Accident Detection in Traffic Video—0
Interaction-Aware Labeled Multi-Bernoulli Filter—0
Interactive Instance Annotation with Siamese Networks—0
Interactive Multi-scale Fusion of 2D and 3D Features for Multi-object Tracking—0
InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling—0
Interpretable Deep Tracking—0
InterTracker: Discovering and Tracking General Objects Interacting with Hands in the Wild—0
InterTrack: Interaction Transformer for 3D Multi-Object Tracking—0
Introducing HOT3D: An Egocentric Dataset for 3D Hand and Object Tracking—0
Introduction of a tree-based technique for efficient and real-time label retrieval in the object tracking system—0
Inverse Neural Rendering for Explainable Multi-Object Tracking—0
IP-MOT: Instance Prompt Learning for Cross-Domain Multi-Object Tracking—0
ISAR: A Benchmark for Single- and Few-Shot Object Instance Segmentation and Re-Identification—0
Is First Person Vision Challenging for Object Tracking?—0
Is First Person Vision Challenging for Object Tracking?—0
Is Multiple Object Tracking a Matter of Specialization?—0
Isometric Multi-Shape Matching—0
Iterative hypothesis testing for multi-object tracking in presence of features with variable reliability—0
Jacobian Computation for Cumulative B-Splines on SE(3) and Application to Continuous-Time Object Tracking—0
Joint 3D Reconstruction of a Static Scene and Moving Objects—0
PTP: Parallelized Tracking and Prediction with Graph Neural Networks and Diversity Sampling—0
Joint Graph Decomposition & Node Labeling: Problem, Algorithms, Applications—0
Joint Inference of States, Robot Knowledge, and Human (False-)Beliefs—0
Joint Learning of Siamese CNNs and Temporally Constrained Metrics for Tracklet Association—0
Joint Scene and Object Tracking for Cost-Effective Augmented Reality Assisted Patient Positioning in Radiation Therapy—0
Joint Spatial-Temporal Calibration for Camera and Global Pose Sensor—0
Joint Spatial-Temporal Optimization for Stereo 3D Object Tracking—0
Keypoint-based object tracking and localization using networks of low-power embedded smart cameras—0
Know Your Surroundings: Exploiting Scene Information for Object Tracking—0
Know Your Surroundings: Panoramic Multi-Object Tracking by Multimodality Collaboration—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