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/franktpmvu/NeighborTrack
공식 코드NeighborTrack: Improving Single Object Tracking by Bipartite Matching with Neighbor Tracklets
https://github.com/fredfung007/cityflow-nl
공식 코드CityFlow-NL: Tracking and Retrieval of Vehicles at City Scale by Natural Language Descriptions
https://github.com/fredfung007/snlt
공식 코드Siamese Natural Language Tracker: Tracking by Natural Language Descriptions with Siamese Trackers
https://github.com/fregu856/ebms_regression
공식 코드https://github.com/fubel/stmc
공식 코드Spatial-Temporal Multi-Cuts for Online Multiple-Camera Vehicle Tracking
https://github.com/fubel/synthehicle
공식 코드Synthehicle: Multi-Vehicle Multi-Camera Tracking in Virtual Cities
https://github.com/funkelab/linajea
공식 코드Tracking by weakly-supervised learning and graph optimization for whole-embryo C. elegans lineages
https://github.com/fzh0917/STMTrack
공식 코드STMTrack: Template-free Visual Tracking with Space-time Memory Networks
https://github.com/fzi-forschungszentrum-informatik/NNAD
공식 코드https://github.com/gafaua/polytrack
공식 코드https://github.com/gakkistar/fishmot
공식 코드FishMOT: A Simple and Effective Method for Fish Tracking Based on IoU Matching
https://github.com/ganlab/ostra
공식 코드A One Stop 3D Target Reconstruction and multilevel Segmentation Method
https://github.com/gaoangw/TC_tracker
공식 코드https://github.com/gaomingqi/track-anything
공식 코드https://github.com/georgedeath/initialisation-problem
공식 코드https://github.com/gerardmaggiolino/deep-oc-sort
공식 코드Deep OC-SORT: Multi-Pedestrian Tracking by Adaptive Re-Identification
https://github.com/gerdm/weighted-likelihood-filter
공식 코드https://github.com/gewelsji/vps
공식 코드https://github.com/ghostish/open3dsot
공식 코드Box-Aware Feature Enhancement for Single Object Tracking on Point Clouds
https://github.com/giantai/pixtrack
공식 코드PixTrack: Precise 6DoF Object Pose Tracking using NeRF Templates and Feature-metric Alignment
https://github.com/git-disl/emo
공식 코드Fast and Resource-Efficient Object Tracking on Edge Devices: A Measurement Study
https://github.com/gitmehrdad/sfsort
공식 코드SFSORT: Scene Features-based Simple Online Real-Time Tracker
https://github.com/google-research-datasets/Objectron
공식 코드Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose Annotations
https://github.com/google-research/google-research
공식 코드Unsupervised Learning of Object Structure and Dynamics from Videos
https://github.com/got-10k/toolkit
공식 코드GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild
https://github.com/goutamyg/mvt
공식 코드https://github.com/goutamyg/smat
공식 코드Separable Self and Mixed Attention Transformers for Efficient Object Tracking
https://github.com/greatenanoymous/rgbtrack
공식 코드RGBTrack: Fast, Robust Depth-Free 6D Pose Estimation and Tracking
https://github.com/guanxiongsun/stpn
공식 코드Spatio-temporal Prompting Network for Robust Video Feature Extraction
https://github.com/guanxiongsun/vfe.pytorch
공식 코드Spatio-temporal Prompting Network for Robust Video Feature Extraction
https://github.com/gxnu-zhonglab/mambalct
공식 코드MambaLCT: Boosting Tracking via Long-term Context State Space Model
https://github.com/gxnu-zhonglab/odtrack
공식 코드ODTrack: Online Dense Temporal Token Learning for Visual Tracking
https://github.com/hadi-ghnd/accidentdetection
공식 코드Real-Time Accident Detection in Traffic Surveillance Using Deep Learning
https://github.com/hailanyi/virconv
공식 코드Virtual Sparse Convolution for Multimodal 3D Object Detection
https://github.com/hakanardo/ggdtrack
공식 코드Multi Target Tracking by Learning from Generalized Graph Differences
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.