https://github.com/openspaceai/uvltrack
공식 코드Unifying Visual and Vision-Language Tracking via Contrastive Learning
Papers with Code 아카이브
Object Tracking
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 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/oronnir/cast
공식 코드CAST: Character labeling in Animation using Self-supervision by Tracking
https://github.com/ostadabbas/multiple-toddler-tracking
공식 코드https://github.com/pblatter/ettrack
공식 코드https://github.com/pbonazzi/retina
공식 코드Retina : Low-Power Eye Tracking with Event Camera and Spiking Hardware
https://github.com/pfdp0/ContrasTR
공식 코드Contrastive Learning for Multi-Object Tracking with Transformers
https://github.com/phi-wol/hydra
공식 코드Unleashing HyDRa: Hybrid Fusion, Depth Consistency and Radar for Unified 3D Perception
https://github.com/phil-bergmann/tracking_wo_bnw
공식 코드https://github.com/phiphiphi31/DMB
공식 코드Learning Spatio-Appearance Memory Network for High-Performance Visual Tracking
https://github.com/phiphiphi31/SBT
공식 코드https://github.com/phiphiphi31/dualtfr
공식 코드Learning Tracking Representations via Dual-Branch Fully Transformer Networks
https://github.com/pholypeng/pnas-mot
공식 코드PNAS-MOT: Multi-Modal Object Tracking with Pareto Neural Architecture Search
https://github.com/piecezhang/motiondctrack
공식 코드https://github.com/pinatafarms/feartracker
공식 코드https://github.com/pingyang1117/PRBNet_PyTorch
공식 코드Parallel Residual Bi-Fusion Feature Pyramid Network for Accurate Single-Shot Object Detection
https://github.com/pingyang1117/smiletrack_official
공식 코드SMILEtrack: SiMIlarity LEarning for Occlusion-Aware Multiple Object Tracking
https://github.com/pjl1995/CTracker
공식 코드https://github.com/pjlab-adg/detzero
공식 코드DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point Clouds
https://github.com/pmcesky/4d-cell
공식 코드Prediction of Cellular Identities from Trajectory and Cell Fate Information
https://github.com/pmixer/tracker.eval
공식 코드https://github.com/pondruska/DeepTracking
공식 코드Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks
https://github.com/poodarchu/efg
공식 코드TrajectoryFormer: 3D Object Tracking Transformer with Predictive Trajectory Hypotheses
https://github.com/psaltaath/tadn-mot
공식 코드Transformer-based assignment decision network for multiple object tracking
https://github.com/pxiangwu/MotionNet
공식 코드Joint Perception and Prediction for Autonomous Driving: A Survey
https://github.com/q2479036243/must-multispectral-uav-single-object-tracking
공식 코드MUST: The First Dataset and Unified Framework for Multispectral UAV Single Object Tracking
https://github.com/qa276390/searchtrack
공식 코드SearchTrack: Multiple Object Tracking with Object-Customized Search and Motion-Aware Features
https://github.com/qcraftai/simtrack
공식 코드Exploring Simple 3D Multi-Object Tracking for Autonomous Driving
https://github.com/qinche106/cb-convlstm-eyetracking
공식 코드3ET: Efficient Event-based Eye Tracking using a Change-Based ConvLSTM Network
https://github.com/qingyonghu/viso
공식 코드Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark
https://github.com/qinzheng2000/generaltrack
공식 코드https://github.com/quinngroup/3Dcell_tracking_DSAA2019
공식 코드Lightweight and Scalable Particle Tracking and Motion Clustering of 3D Cell Trajectories
https://github.com/radarcamerafusionteam-bupt/es-eot
공식 코드3D Extended Object Tracking by Fusing Roadside Sparse Radar Point Clouds and Pixel Keypoints
https://github.com/raileye3d/raileye3d_dataset
공식 코드RGB-D Railway Platform Monitoring and Scene Understanding for Enhanced Passenger Safety
https://github.com/rainbowluocs/diffusiontrack
공식 코드https://github.com/ramtin-ma/videosynopsis-fgs
공식 코드A Low-Computational Video Synopsis Framework with a Standard Dataset
https://github.com/raphaelreme/sinetra
공식 코드SINETRA: a Versatile Framework for Evaluating Single Neuron Tracking in Behaving Animals
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.