https://github.com/tensorflow/models
공식 코드Contextualized Spatio-Temporal Contrastive Learning with Self-Supervision
Papers with Code 아카이브
Object Tracking
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- 평가표
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- 보존된 평가 기록
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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/tfwu/RGM-AOGTracker
공식 코드Online Object Tracking, Learning and Parsing with And-Or Graphs
https://github.com/tianweiy/CenterPoint
공식 코드https://github.com/timbervision/timbervision
공식 코드https://github.com/timmeinhardt/trackformer
공식 코드https://github.com/timok93/aplift
공식 코드Making Higher Order MOT Scalable: An Efficient Approximate Solver for Lifted Disjoint Paths
https://github.com/timok93/biologicalneeds
공식 코드https://github.com/timothygebhard/hsr4hci
공식 코드https://github.com/tmandel/fish-detrac
공식 코드Reliable Multi-Object Tracking in the Presence of Unreliable Detections
https://github.com/tobiasfshr/MOTSFusion
공식 코드https://github.com/toptrack/toptrack2023
공식 코드https://github.com/trailab/uncertaintytrack
공식 코드UncertaintyTrack: Exploiting Detection and Localization Uncertainty in Multi-Object Tracking
https://github.com/transmuteai/implicit-networks
공식 코드https://github.com/transmuteai/light-weight-trackers
공식 코드On Designing Light-Weight Object Trackers through Network Pruning: Use CNNs or Transformers?
https://github.com/tri-ml/pf-track
공식 코드Standing Between Past and Future: Spatio-Temporal Modeling for Multi-Camera 3D Multi-Object Tracking
https://github.com/trojerz/trans2k
공식 코드Trans2k: Unlocking the Power of Deep Models for Transparent Object Tracking
https://github.com/tsinghua-mars-lab/geomae
공식 코드GeoMAE: Masked Geometric Target Prediction for Self-supervised Point Cloud Pre-Training
https://github.com/tsinghua-mars-lab/trackocc
공식 코드https://github.com/tsingqguo/ABA
공식 코드https://github.com/tsingqguo/robustot
공식 코드LRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks
https://github.com/tteepe/EarlyBird
공식 코드EarlyBird: Early-Fusion for Multi-View Tracking in the Bird's Eye View
https://github.com/tteepe/tracktacular
공식 코드Lifting Multi-View Detection and Tracking to the Bird's Eye View
https://github.com/tudelft-iv-students/offline-tracking-with-object-permanence
공식 코드https://github.com/tusen-ai/sst
공식 코드FSD V2: Improving Fully Sparse 3D Object Detection with Virtual Voxels
https://github.com/tusimple/simpletrack
공식 코드SimpleTrack: Understanding and Rethinking 3D Multi-object Tracking
https://github.com/tvpian/project-tar
공식 코드https://github.com/uark-cviu/DyGLIP
공식 코드https://github.com/ucla-mobility/v2v4real
공식 코드V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perception
https://github.com/umich-bipedlab/optimal_shape_generation
공식 코드https://github.com/umich-bipedlab/optimal_shape_global_pose_estimation
공식 코드https://github.com/utn-blei/cloudtrack
공식 코드https://github.com/vghost2008/sportstrack
공식 코드SportsTrack: An Innovative Method for Tracking Athletes in Sports Scenes
https://github.com/vision4robotics/ADTrack
공식 코드ADTrack: Target-Aware Dual Filter Learning for Real-Time Anti-Dark UAV Tracking
https://github.com/vision4robotics/ADTrack_v2
공식 코드https://github.com/vision4robotics/ARCF-tracker
공식 코드Learning Aberrance Repressed Correlation Filters for Real-Time UAV Tracking
https://github.com/vision4robotics/BEVT-tracker
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.