https://github.com/MICV-yonsei/DragText
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold
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/QiHuangChen/CACFNet
DCFNet: Discriminant Correlation Filters Network for Visual Tracking
https://github.com/STVIR/pysot
SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks
https://github.com/ShuaiBai623/MFT
Multi-hierarchical Independent Correlation Filters for Visual Tracking
https://github.com/VisualComputingInstitute/SiamR-CNN
https://github.com/ZekuiQin/SiamKPN
SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines
https://github.com/adriaciurana/DragGAN
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold
https://github.com/aharley/pips2
PointOdyssey: A Large-Scale Synthetic Dataset for Long-Term Point Tracking
https://github.com/ailovejinx/gsot3d
https://github.com/championway/re3_tracking
Re3 : Real-Time Recurrent Regression Networks for Visual Tracking of Generic Objects
https://github.com/chikuanlin/re3-pytorch
Re3 : Real-Time Recurrent Regression Networks for Visual Tracking of Generic Objects
https://github.com/code-implementation1/Code8/tree/main/SiamFC
SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines
https://github.com/code-implementation1/Code8/tree/main/sknet
https://github.com/codecolony/re3-tensorflow
Re3 : Real-Time Recurrent Regression Networks for Visual Tracking of Generic Objects
https://github.com/cuixing100876/instastyle
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold
https://github.com/danielgordon10/re3-tensorflow
Re3 : Real-Time Recurrent Regression Networks for Visual Tracking of Generic Objects
https://github.com/dscv-lab/KMF2JMTtracking
Robust Visual Tracking using Multi-Frame Multi-Feature Joint Modeling
https://github.com/dsl-lab/fvmd-frechet-video-motion-distance
Fréchet Video Motion Distance: A Metric for Evaluating Motion Consistency in Videos
https://github.com/eowjd0512/VITAMIN-E
VITAMIN-E: VIsual Tracking And MappINg with Extremely Dense Feature Points
https://github.com/ezelikman/anonymal
Fast Online Object Tracking and Segmentation: A Unifying Approach
https://github.com/facebookresearch/vggsfm
https://github.com/foolwood/SiamMask
Fast Online Object Tracking and Segmentation: A Unifying Approach
https://github.com/godcrampy/re3-custom
Re3 : Real-Time Recurrent Regression Networks for Visual Tracking of Generic Objects
https://github.com/google-deepmind/perception_test
https://github.com/hibetterheyj/Note-Everyday
Learning regression and verification networks for long-term visual tracking
https://github.com/hibetterheyj/Paper-Everyday
Learning regression and verification networks for long-term visual tracking
https://github.com/hutgun11/muti_object_tracking_re3
Re3 : Real-Time Recurrent Regression Networks for Visual Tracking of Generic Objects
https://github.com/huzexi/huzexi
https://github.com/hyperparameters/tracking_via_colorization
https://github.com/ibaiGorordo/Tapir-Pytorch-Inference
TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinement
https://github.com/kibernetika-ai/re3-tensorflow
Re3 : Real-Time Recurrent Regression Networks for Visual Tracking of Generic Objects
https://github.com/ku-cvlab/locotrack
https://github.com/laisimiao/MambaVT
MambaVT: Spatio-Temporal Contextual Modeling for robust RGB-T Tracking
https://github.com/large-trajectory-model/atm
https://github.com/linzhi123/DCFNet
DCFNet: Discriminant Correlation Filters Network for Visual Tracking
https://github.com/linzhi123/DCFNet-pytouch
DCFNet: Discriminant Correlation Filters Network for Visual Tracking
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.