{"total":46,"rows":[{"id":"2202.13514","title":"StrongSORT: Make DeepSORT Great Again","created":"2022-02-28","cited_by_count":213,"area":null},{"id":"2111.09621","title":"SimpleTrack: Understanding and Rethinking 3D Multi-object Tracking","created":"2021-11-18","cited_by_count":103,"area":null},{"id":"2203.06398","title":"SIGMA: Semantic-complete Graph Matching for Domain Adaptive Object Detection","created":"2022-03-12","cited_by_count":74,"area":null},{"id":"2308.00783","title":"Hybrid-SORT: Weak Cues Matter for Online Multi-Object Tracking","created":"2023-08-01","cited_by_count":67,"area":null},{"id":"2303.10404","title":"MotionTrack: Learning Robust Short-term and Long-term Motions for Multi-Object Tracking","created":"2023-03-18","cited_by_count":64,"area":null},{"id":"2212.03038","title":"Unifying Short and Long-Term Tracking with Graph Hierarchies","created":"2022-12-06","cited_by_count":62,"area":null},{"id":"2306.05238","title":"SparseTrack: Multi-Object Tracking by Performing Scene Decomposition based on Pseudo-Depth","created":"2023-06-08","cited_by_count":48,"area":null},{"id":"2111.13672","title":"Immortal Tracker: Tracklet Never Dies","created":"2021-11-26","cited_by_count":42,"area":null},{"id":"2207.05518","title":"Tracking Objects as Pixel-wise Distributions","created":"2022-07-12","cited_by_count":37,"area":null},{"id":"2203.14208","title":"Towards Discriminative Representation: Multi-view Trajectory Contrastive Learning for Online Multi-object Tracking","created":"2022-03-27","cited_by_count":33,"area":null},{"id":"2112.09828","title":"Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs","created":"2021-12-18","cited_by_count":31,"area":null},{"id":"2207.10047","title":"Densely Constrained Depth Estimator for Monocular 3D Object Detection","created":"2022-07-20","cited_by_count":27,"area":null},{"id":"2406.00429","title":"Towards Generalizable Multi-Object Tracking","created":"2024-06-01","cited_by_count":23,"area":null},{"id":"2105.02426","title":"Split and Connect: A Universal Tracklet Booster for Multi-Object Tracking","created":"2021-05-06","cited_by_count":17,"area":null},{"id":"2212.01568","title":"Generalizing Multiple Object Tracking to Unseen Domains by Introducing Natural Language Representation","created":"2022-12-03","cited_by_count":17,"area":null},{"id":"2201.01297","title":"Online Multi-Object Tracking with Unsupervised Re-Identification Learning and Occlusion Estimation","created":"2022-01-04","cited_by_count":16,"area":null},{"id":"2203.16210","title":"Learning of Global Objective for Network Flow in Multi-Object Tracking","created":"2022-03-30","cited_by_count":11,"area":null},{"id":"2403.19474","title":"SG-PGM: Partial Graph Matching Network with Semantic Geometric Fusion for 3D Scene Graph Alignment and Its Downstream Tasks","created":"2024-03-28","cited_by_count":10,"area":null},{"id":"2207.07454","title":"Multi-Object Tracking and Segmentation via Neural Message Passing","created":"2022-07-15","cited_by_count":9,"area":null},{"id":"2308.09908","title":"LEGO: Learning and Graph-Optimized Modular Tracker for Online Multi-Object Tracking with Point Clouds","created":"2023-08-19","cited_by_count":9,"area":null},{"id":"2403.02767","title":"DeconfuseTrack:Dealing with Confusion for Multi-Object Tracking","created":"2024-03-05","cited_by_count":9,"area":null},{"id":"2205.10766","title":"Recent Advances in Embedding Methods for Multi-Object Tracking: A Survey","created":"2022-05-22","cited_by_count":8,"area":null},{"id":"2312.08951","title":"Multi-Scene Generalized Trajectory Global Graph Solver with Composite Nodes for Multiple Object Tracking","created":"2023-12-14","cited_by_count":7,"area":null},{"id":"2403.06457","title":"Ensemble Quadratic Assignment Network for Graph Matching","created":"2024-03-11","cited_by_count":6,"area":null},{"id":"2501.11288","title":"PD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues","created":"2025-01-20","cited_by_count":6,"area":null},{"id":"2402.16594","title":"CURSOR: Scalable Mixed-Order Hypergraph Matching with CUR Decomposition","created":"2024-02-26","cited_by_count":3,"area":null},{"id":"2509.02111","title":"NOOUGAT: Towards Unified Online and Offline Multi-Object Tracking","created":"2025-09-02","cited_by_count":3,"area":null},{"id":"2306.05416","title":"Tracking Objects with 3D Representation from Videos","created":"2023-06-08","cited_by_count":2,"area":null},{"id":"2312.08671","title":"Permutation-Invariant Graph Partitioning:How Graph Neural Networks Capture Structural Interactions?","created":"2023-12-14","cited_by_count":2,"area":null},{"id":"2404.07553","title":"SFSORT: Scene Features-based Simple Online Real-Time Tracker","created":"2024-04-11","cited_by_count":2,"area":null},{"id":"2507.08494","title":"One Graph to Track Them All: Dynamic GNNs for Single- and Multi-View Tracking","created":"2025-07-11","cited_by_count":2,"area":null},{"id":"2604.12665","title":"Hypergraph-State Collaborative Reasoning for Multi-Object Tracking","created":"2026-04-14","cited_by_count":2,"area":null},{"id":"2208.03571","title":"Transformer-based assignment decision network for multiple object tracking","created":"2022-08-06","cited_by_count":1,"area":null},{"id":"2210.13570","title":"Strong-TransCenter: Improved Multi-Object Tracking based on Transformers with Dense Representations","created":"2022-10-24","cited_by_count":1,"area":null},{"id":"2305.09981","title":"S$^3$Track: Self-supervised Tracking with Soft Assignment Flow","created":"2023-05-17","cited_by_count":0,"area":null},{"id":"2309.01078","title":"UnsMOT: Unified Framework for Unsupervised Multi-Object Tracking with Geometric Topology Guidance","created":"2023-09-03","cited_by_count":0,"area":null},{"id":"2310.12407","title":"Classification-Aided Robust Multiple Target Tracking Using Neural Enhanced Message Passing","created":"2023-10-19","cited_by_count":0,"area":null},{"id":"2402.04275","title":"Motion Mapping Cognition: A Nondecomposable Primary Process in Human Vision","created":"2024-02-02","cited_by_count":0,"area":null},{"id":"2402.12968","title":"MapTrack: Tracking in the Map","created":"2024-02-20","cited_by_count":0,"area":null},{"id":"2407.04308","title":"SSP-GNN: Learning to Track via Bilevel Optimization","created":"2024-07-05","cited_by_count":0,"area":null},{"id":"2410.17101","title":"CLAP: Concave Linear APproximation for Quadratic Graph Matching","created":"2024-10-22","cited_by_count":0,"area":null},{"id":"2503.23806","title":"Bridge the Gap Between Visual and Linguistic Comprehension for Generalized Zero-shot Semantic Segmentation","created":"2025-03-31","cited_by_count":0,"area":null},{"id":"2508.00887","title":"FRAM: Frobenius-Regularized Assignment Matching with Mixed-Precision Computing","created":"2025-07-26","cited_by_count":0,"area":null},{"id":"2508.11323","title":"Delving into Dynamic Scene Cue-Consistency for Robust 3D Multi-Object Tracking","created":"2025-08-15","cited_by_count":0,"area":null},{"id":"2508.14607","title":"SMTrack: End-to-End Trained Spiking Neural Networks for Multi-Object Tracking in RGB Videos","created":"2025-08-20","cited_by_count":0,"area":null},{"id":"2606.30476","title":"PS-MOT: Cultivating Instance Awareness from Point Seeds for Multi-Object Tracking","created":"2026-06-29","cited_by_count":0,"area":null}],"next_cursor":null}