Papers with Code 아카이브
Visual Tracking
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 4
- 평가표
- 10
- 보존된 평가 기록
- 19
Visual Tracking is an essential and actively researched problem in the field of computer vision with various real-world applications such as robotic services, smart surveillance systems, autonomous driving, and human-computer interaction. It refers to the automatic estimation of the trajectory of an arbitrary target object, usually specified by a bounding box in the first frame, as it moves around in subsequent video frames.
Source: Learning Reinforced Attentional Representation for End-to-End Visual Tracking
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/amgao/rls-onlinetrack
공식 코드Recursive Least-Squares Estimator-Aided Online Learning for Visual Tracking
https://github.com/amir-abdi/artisynth_point2point
공식 코드Muscle Excitation Estimation in Biomechanical Simulation Using NAF Reinforcement Learning
https://github.com/artemcher/myotracker
공식 코드Low Complexity Point Tracking of the Myocardium in 2D Echocardiography
https://github.com/athaddius/stirmetrics
공식 코드Point Tracking in Surgery--The 2024 Surgical Tattoos in Infrared (STIR) Challenge
https://github.com/ayshrv/gmrw
공식 코드Self-Supervised Any-Point Tracking by Contrastive Random Walks
https://github.com/basilevh/tcow
공식 코드https://github.com/basitalawode/uwvot400
공식 코드Improving Underwater Visual Tracking With a Large Scale Dataset and Image Enhancement
https://github.com/botaoye/ostrack
공식 코드Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework
https://github.com/braincorp/ASC
공식 코드https://github.com/braincorp/PVM
공식 코드Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network
https://github.com/caibolun/BIT
공식 코드https://github.com/cardio-ai/mvhota
공식 코드https://github.com/cbellinger27/bendrl_reacher_tracker
공식 코드Learning Visual Tracking and Reaching with Deep Reinforcement Learning on a UR10e Robotic Arm
https://github.com/chaoma99/HCFTstar
공식 코드Robust Visual Tracking via Hierarchical Convolutional Features
https://github.com/chenshihfang/GOT
공식 코드https://github.com/chenxin-dlut/TransT
공식 코드https://github.com/chenxin-dlut/hcat
공식 코드Efficient Visual Tracking via Hierarchical Cross-Attention Transformer
https://github.com/chenxin-dlut/seqtrackv2
공식 코드Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking
https://github.com/chenxin-dlut/sutrack
공식 코드https://github.com/chizhizhen/DNT
공식 코드https://github.com/coltonstearns/dynamic-gaussian-marbles
공식 코드Dynamic Gaussian Marbles for Novel View Synthesis of Casual Monocular Videos
https://github.com/cswaynecool/DRT
공식 코드Correlation Tracking via Joint Discrimination and Reliability Learning
https://github.com/cswaynecool/LSART
공식 코드https://github.com/cvlab-kaist/Chrono
공식 코드https://github.com/cvlab-kaist/locotrack
공식 코드https://github.com/cvlab-kaist/seurat
공식 코드https://github.com/daikenan/vasr
공식 코드Video Annotation for Visual Tracking via Selection and Refinement
https://github.com/dawnyc/romtrack
공식 코드https://github.com/dcharatan/flowmap
공식 코드FlowMap: High-Quality Camera Poses, Intrinsics, and Depth via Gradient Descent
https://github.com/deepmind/perception_test
공식 코드Perception Test: A Diagnostic Benchmark for Multimodal Video Models
https://github.com/deepmind/tapnet
공식 코드https://github.com/dinghaoxuan/oneshotlp
공식 코드A Training-Free Framework for Video License Plate Tracking and Recognition with Only One-Shot
https://github.com/dlr-rm/3dobjecttracking
공식 코드SRT3D: A Sparse Region-Based 3D Object Tracking Approach for the Real World
https://github.com/dongzhou-1996/sncoat
공식 코드Space Non-cooperative Object Active Tracking with Deep Reinforcement Learning
https://github.com/dontfollowmeimcrazy/vot-kd-rl
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.