https://github.com/robindsyang/DivaTrack
공식 코드DivaTrack: Diverse Bodies and Motions from Acceleration-Enhanced Three-Point Trackers
Papers with Code 아카이브
Point Tracking
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Point Tracking, often referred to as Tracking any Point (TAP) involves acquiring, focusing on, and continuously tracking specific target point/points across video frames. The system identifies the target point, maintains focus, and predicts its movement, enabling smooth tracking even if the target moves unpredictably, or through occlusions. TAP has wide applications like object tracking, surveillance, and autonomous navigation.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/serycjon/MFT
공식 코드https://github.com/skoltech-paco/linearbatterymodels
공식 코드https://github.com/skyesong38/altrack
공식 코드https://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/tub-rip/motionpriorcmax
공식 코드Motion-prior Contrast Maximization for Dense Continuous-Time Motion Estimation
https://github.com/wrchen530/leapvo
공식 코드LEAP-VO: Long-term Effective Any Point Tracking for Visual Odometry
https://github.com/wuzijian1997/sis-pt-sam
공식 코드https://github.com/wyddmw/pomato
공식 코드POMATO: Marrying Pointmap Matching with Temporal Motion for Dynamic 3D Reconstruction
https://github.com/y-zheng18/point_odyssey
공식 코드PointOdyssey: A Large-Scale Synthetic Dataset for Long-Term Point Tracking
https://github.com/zbw001/tapip3d
공식 코드https://bitbucket.org/nordlinglab/nordlinglab-dfe
https://github.com/MICV-yonsei/DragText
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold
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/cuixing100876/instastyle
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold
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/facebookresearch/vggsfm
https://github.com/google-deepmind/perception_test
https://github.com/ibaiGorordo/Tapir-Pytorch-Inference
TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinement
https://github.com/ku-cvlab/locotrack
https://github.com/large-trajectory-model/atm
https://github.com/opengvlab/internchat
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold
https://github.com/opengvlab/interngpt
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold
https://github.com/saic-mdal/HiDT
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.