https://github.com/haooozi/P2P
공식 코드P2P: Part-to-Part Motion Cues Guide a Strong Tracking Framework for LiDAR Point Clouds
Papers with Code 아카이브
Object Tracking
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 10
- 평가표
- 10
- 보존된 평가 기록
- 43
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/haooozi/glt-t
공식 코드GLT-T: Global-Local Transformer Voting for 3D Single Object Tracking in Point Clouds
https://github.com/haooozi/osp2b
공식 코드OSP2B: One-Stage Point-to-Box Network for 3D Siamese Tracking
https://github.com/hasanirtiza/Pedestron
공식 코드Pedestrian Detection: Domain Generalization, CNNs, Transformers and Beyond
https://github.com/hdu-vrlab/siammo
공식 코드https://github.com/hejiawei2023/ug3dmot
공식 코드3D Multi-Object Tracking Based on Uncertainty-Guided Data Association
https://github.com/hekaijie123/TATrack
공식 코드https://github.com/helicopt/framot
공식 코드https://github.com/henglan/vasttrack
공식 코드https://github.com/henningtjaden/RBOT
공식 코드A Region-based Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking
https://github.com/heruihr/rallytrack
공식 코드D$^{\bf{3}}$: Duplicate Detection Decontaminator for Multi-Athlete Tracking in Sports Videos
https://github.com/hkchengrex/Cutie
공식 코드https://github.com/holmescao/TOPICTrack
공식 코드https://github.com/hon-wong/elysium
공식 코드Elysium: Exploring Object-level Perception in Videos via MLLM
https://github.com/hoqolo/sdstrack
공식 코드SDSTrack: Self-Distillation Symmetric Adapter Learning for Multi-Modal Visual Object Tracking
https://github.com/hou-yz/DeepCC-local
공식 코드Locality Aware Appearance Metric for Multi-Target Multi-Camera 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/hsiangwei0903/SportsMOT
공식 코드Observation Centric and Central Distance Recovery on Sports Player Tracking
https://github.com/huajianup/360vot
공식 코드360VOT: A New Benchmark Dataset for Omnidirectional Visual Object Tracking
https://github.com/huckiyang/MOT-Kuzushiji-Fashion-Video
공식 코드Robust Unsupervised Multi-Object Tracking in Noisy Environments
https://github.com/hustdml/cttrack
공식 코드Compact Transformer Tracker with Correlative Masked Modeling
https://github.com/husteryoung/mplt
공식 코드https://github.com/hustvl/sparsetrack
공식 코드SparseTrack: Multi-Object Tracking by Performing Scene Decomposition based on Pseudo-Depth
https://github.com/huuuuusy/videocube-toolkit
공식 코드https://github.com/hwcao17/pkf
공식 코드PKF: Probabilistic Data Association Kalman Filter for Multi-Object Tracking
https://github.com/hxzhong1997/fsba
공식 코드https://github.com/hyunjs/sgt
공식 코드Detection Recovery in Online Multi-Object Tracking with Sparse Graph Tracker
https://github.com/iai-hrc/ha-vid
공식 코드HA-ViD: A Human Assembly Video Dataset for Comprehensive Assembly Knowledge Understanding
https://github.com/ibm/optflow-region-tracker
공식 코드A Real-Time Region Tracking Algorithm Tailored to Endoscopic Video with Open-Source Implementation
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/ihpdep/LDES
공식 코드Robust Estimation of Similarity Transformation for Visual Object Tracking
https://github.com/immortaltracker/immortaltracker
공식 코드https://github.com/inakierregueab/yolo11-jde
공식 코드YOLO11-JDE: Fast and Accurate Multi-Object Tracking with Self-Supervised Re-ID
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.