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Multiple Object Tracking
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Multiple Object Tracking is the problem of automatically identifying multiple objects in a video and representing them as a set of trajectories with high accuracy.
Source: SOT for MOT
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/amazon-science/object-centric-multiple-object-tracking
공식 코드https://github.com/amitgalor18/stc_tracker
공식 코드Strong-TransCenter: Improved Multi-Object Tracking based on Transformers with Dense Representations
https://github.com/autonomousvision/kitti360labeltool
공식 코드KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D
https://github.com/autonomousvision/kitti360scripts
공식 코드KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D
https://github.com/balabooooo/aed
공식 코드Associate Everything Detected: Facilitating Tracking-by-Detection to the Unknown
https://github.com/bdd100k/bdd100k
공식 코드BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
https://github.com/bjoern-andres/graph
공식 코드Joint Graph Decomposition and Node Labeling: Problem, Algorithms, Applications
https://github.com/celltrackingchallenge/py-ctcmetrics
공식 코드https://github.com/chen-si-jia/Trajectory-Long-tail-Distribution-for-MOT
공식 코드Delving into the Trajectory Long-tail Distribution for Muti-object Tracking
https://github.com/cliffordlab/edgecameratracking
공식 코드https://github.com/corfyi/ucmctrack
공식 코드UCMCTrack: Multi-Object Tracking with Uniform Camera Motion Compensation
https://github.com/cuppp1998/360_object_tracking
공식 코드Multiple Object Detection and Tracking in Panoramic Videos for Cycling Safety Analysis
https://github.com/daip13/LPC_MOT
공식 코드https://github.com/dlr-rm/3dobjecttracking
공식 코드SRT3D: A Sparse Region-Based 3D Object Tracking Approach for the Real World
https://github.com/dvl-tum/SUSHI
공식 코드Unifying Short and Long-Term Tracking with Graph Hierarchies
https://github.com/dyhBUPT/GIAOTracker
공식 코드https://github.com/dyhbupt/ensemblemot
공식 코드EnsembleMOT: A Step towards Ensemble Learning of Multiple Object Tracking
https://github.com/emirhanbayar/fast-deep-oc-sort
공식 코드When to Extract ReID Features: A Selective Approach for Improved Multiple Object Tracking
https://github.com/emirhanbayar/fast-strongsort
공식 코드When to Extract ReID Features: A Selective Approach for Improved Multiple Object Tracking
https://github.com/fandulu/asad
공식 코드Actor-identified Spatiotemporal Action Detection --- Detecting Who Is Doing What in Videos
https://github.com/flowerfan/trackron
공식 코드https://github.com/fubel/stmc
공식 코드Spatial-Temporal Multi-Cuts for Online Multiple-Camera Vehicle Tracking
https://github.com/gakkistar/fishmot
공식 코드FishMOT: A Simple and Effective Method for Fish Tracking Based on IoU Matching
https://github.com/hailanyi/virconv
공식 코드Virtual Sparse Convolution for Multimodal 3D Object Detection
https://github.com/henningtjaden/RBOT
공식 코드A Region-based Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking
https://github.com/hqucv/dmtrack
공식 코드Distractor-Aware Fast Tracking via Dynamic Convolutions and MOT Philosophy
https://github.com/hsiangwei0903/Deep-EIoU
공식 코드Iterative Scale-Up ExpansionIoU and Deep Features Association for Multi-Object Tracking in Sports
https://github.com/hustvl/sparsetrack
공식 코드SparseTrack: Multi-Object Tracking by Performing Scene Decomposition based on Pseudo-Depth
https://github.com/icicle4/transtam
공식 코드Joint Spatial-Temporal and Appearance Modeling with Transformer for Multiple Object Tracking
https://github.com/ifzhang/ByteTrack
공식 코드ByteTrack: Multi-Object Tracking by Associating Every Detection Box
https://github.com/ifzhang/FairMOT
공식 코드FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking
https://github.com/iyybpatrick/MKCF
공식 코드Multiple Object Tracking with Kernelized Correlation Filters in Urban Mixed Traffic
https://github.com/jiaweihe1996/GMTracker
공식 코드https://github.com/jinyanglii/ovtr
공식 코드OVTR: End-to-End Open-Vocabulary Multiple Object Tracking with Transformer
https://github.com/kemo-huang/bitrack
공식 코드BiTrack: Bidirectional Offline 3D Multi-Object Tracking Using Camera-LiDAR Data
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.