https://github.com/ofsoundof/Heterogeneity_Hypothesis
공식 코드The Heterogeneity Hypothesis: Finding Layer-Wise Differentiated Network Architectures
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/ohhhyeahhh/SiamCAR
공식 코드SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking
https://github.com/openat25/hiptrack-mls
공식 코드https://github.com/opencodegithub/h-dcpt
공식 코드https://github.com/openspaceai/uvltrack
공식 코드Unifying Visual and Vision-Language Tracking via Contrastive Learning
https://github.com/pblatter/ettrack
공식 코드https://github.com/pgao-lab/DiffDf
공식 코드Towards Effective and Efficient Adversarial Defense with Diffusion Models for Robust Visual Tracking
https://github.com/pgao-lab/amga
공식 코드Towards Adaptive Meta-Gradient Adversarial Examples for Visual Tracking
https://github.com/phiphiphi31/DMB
공식 코드Learning Spatio-Appearance Memory Network for High-Performance Visual Tracking
https://github.com/piecezhang/motiondctrack
공식 코드https://github.com/pmixer/tracker.eval
공식 코드https://github.com/psaltaath/tadn-mot
공식 코드Transformer-based assignment decision network for multiple object tracking
https://github.com/qianduoduolr/decomotion
공식 코드https://github.com/quickhdsdc/Point-Tracking-for-Displacement-Measurement-in-Railway-Applications
공식 코드https://github.com/rehglab/tracking_objectness
공식 코드https://github.com/researchmm/SiamDW
공식 코드Deeper and Wider Siamese Networks for Real-Time Visual Tracking
https://github.com/researchmm/Stark
공식 코드https://github.com/riponazad/echotracker
공식 코드EchoTracker: Advancing Myocardial Point Tracking in Echocardiography
https://github.com/robindsyang/DivaTrack
공식 코드DivaTrack: Diverse Bodies and Motions from Acceleration-Enhanced Three-Point Trackers
https://github.com/rumsyx/RPCF
공식 코드https://github.com/sansanfree/rbo
공식 코드https://github.com/serycjon/MFT
공식 코드https://github.com/serycjon/mftiq
공식 코드MFTIQ: Multi-Flow Tracker with Independent Matching Quality Estimation
https://github.com/shallowtoil/DROL
공식 코드Discriminative and Robust Online Learning for Siamese Visual Tracking
https://github.com/skoltech-paco/linearbatterymodels
공식 코드https://github.com/skyesong38/altrack
공식 코드https://github.com/skyoung/MemTrack
공식 코드https://github.com/sparktempest/bat
공식 코드https://github.com/stevenwudi/KMC_cvprw_2017
공식 코드https://github.com/supertyd/XTrack
공식 코드XTrack: Multimodal Training Boosts RGB-X Video Object Trackers
https://github.com/sylvie-x/draglora
공식 코드DragLoRA: Online Optimization of LoRA Adapters for Drag-based Image Editing in Diffusion Model
https://github.com/syscv/sam-pt
공식 코드https://github.com/tchuanm/avitmp
공식 코드AViTMP: A Tracking-Specific Transformer for Single-Branch Visual Tracking
https://github.com/tongtybj/TrTr
공식 코드https://github.com/tsingqguo/ABA
공식 코드https://github.com/tsingwei/litetrack
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.