Papers with Code 아카이브
Object Tracking
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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.
<span style="color:grey; opacity: 0.6">( Image credit: Towards-Realtime-MOT )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yinjunbo/UMA-MOT
공식 코드A Unified Object Motion and Affinity Model for Online Multi-Object Tracking
https://github.com/ymzis69/HybridSORT
공식 코드Hybrid-SORT: Weak Cues Matter for Online Multi-Object Tracking
https://github.com/yolomax/coltrack
공식 코드Collaborative Tracking Learning for Frame-Rate-Insensitive Multi-Object Tracking
https://github.com/yongxinw/GSDT
공식 코드Joint Object Detection and Multi-Object Tracking with Graph Neural Networks
https://github.com/youngskkim/CRN
공식 코드CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perception
https://github.com/yoxu515/mits
공식 코드Integrating Boxes and Masks: A Multi-Object Framework for Unified Visual Tracking and Segmentation
https://github.com/yu-lab-vt/CINDA
공식 코드Efficient Global Multi-object Tracking Under Minimum-cost Circulation Framework
https://github.com/yuhsuansia/batch-tpmbm-using-mcmc-sampling
공식 코드Markov Chain Monte Carlo Multi-Scan Data Association for Sets of Trajectories
https://github.com/yuhsuansia/trajectory-pmb-eot-bp
공식 코드Trajectory PMB Filters for Extended Object Tracking Using Belief Propagation
https://github.com/yujeong-star/siamevent
공식 코드SiamEvent: Event-based Object Tracking via Edge-aware Similarity Learning with Siamese Networks
https://github.com/yumu-173/siamese-detr
공식 코드https://github.com/yuzhms/streaming-video-model
공식 코드https://github.com/ywu0912/teamcode
공식 코드M3SOT: Multi-frame, Multi-field, Multi-space 3D Single Object Tracking
https://github.com/z-x-yang/AOT
공식 코드Associating Objects with Transformers for Video Object Segmentation
https://github.com/z-x-yang/segment-and-track-anything
공식 코드https://github.com/z-z188/umdatrack
공식 코드UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions
https://github.com/zhang-pengyu/HMFT
공식 코드Visible-Thermal UAV Tracking: A Large-Scale Benchmark and New Baseline
https://github.com/zhang-pengyu/Multimodal-Tracking-Survey
공식 코드Multi-modal Visual Tracking: Review and Experimental Comparison
https://github.com/zhang-pengyu/Multimodal_tracking_survey
공식 코드Multi-modal Visual Tracking: Review and Experimental Comparison
https://github.com/zhang-tao-whu/DVIS
공식 코드1st Place Solution for the 5th LSVOS Challenge: Video Instance Segmentation
https://github.com/zhangyong-tang/dfat
공식 코드Exploring Fusion Strategies for Accurate RGBT Visual Object Tracking
https://github.com/zhangyong-tang/gmmt
공식 코드https://github.com/zhangyong-tang/taat
공식 코드https://github.com/zhanxinrui/hdn
공식 코드Homography Decomposition Networks for Planar Object Tracking
https://github.com/zhen-he/tracking-by-animation
공식 코드Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers
https://github.com/zhenxili96/MFST
공식 코드Multiple Convolutional Features in Siamese Networks for Object Tracking
https://github.com/zhiqic/procontext
공식 코드ProContEXT: Exploring Progressive Context Transformer for Tracking
https://github.com/zikunzhou/saot
공식 코드https://github.com/zillur-av/wrong-way-vehicle-detection
공식 코드A Real-Time Wrong-Way Vehicle Detection Based on YOLO and Centroid Tracking
https://github.com/zitongzhan/mmtracking/tree/zitongzhan/rovis/configs/vis/rovis
공식 코드Robust Online Video Instance Segmentation with Track Queries
https://github.com/zongwei97/untrack
공식 코드https://github.com/zyn213/temprmot
공식 코드https://gitlab.au.dk/maleci/opendr/opendr_internal
공식 코드VPIT: Real-time Embedded Single Object 3D Tracking Using Voxel Pseudo Images
https://gitlab.au.dk/maleci/opendr/variational-voxel-3d-detetction
공식 코드https://gitlab.au.dk/maleci/opendr/vnn_vpit_opendr
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.