https://github.com/prbonn/hortimapping
공식 코드Panoptic Mapping with Fruit Completion and Pose Estimation for Horticultural Robots
Papers with Code 아카이브
Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 17
- 평가표
- 31
- 보존된 평가 기록
- 235
Pose Estimation is a computer vision task where the goal is to detect the position and orientation of a person or an object. Usually, this is done by predicting the location of specific keypoints like hands, head, elbows, etc. in case of Human Pose Estimation.
A common benchmark for this task is MPII Human Pose
<span style="color:grey; opacity: 0.6">( Image credit: Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/prbonn/pin_slam
공식 코드https://github.com/predict-idlab/landmarker
공식 코드landmarker: a Toolkit for Anatomical Landmark Localization in 2D/3D Images
https://github.com/princeton-vl/coupled-iterative-refinement
공식 코드Coupled Iterative Refinement for 6D Multi-Object Pose Estimation
https://github.com/princetonvisualai/hpe-inductive-prior-tuning
공식 코드Efficient, Self-Supervised Human Pose Estimation with Inductive Prior Tuning
https://github.com/prinik/awa-pose
공식 코드A Novel Dataset for Keypoint Detection of quadruped Animals from Images
https://github.com/probcomp/threedp3
공식 코드https://github.com/prosperolo/gst
공식 코드GST: Precise 3D Human Body from a Single Image with Gaussian Splatting Transformers
https://github.com/proteus1991/RawVSR
공식 코드Exploit Camera Raw Data for Video Super-Resolution via Hidden Markov Model Inference
https://github.com/pshams55/AMIL
공식 코드AMIL: Adversarial Multi Instance Learning for Human Pose Estimation
https://github.com/psyai-net/EmoTalk_release
공식 코드EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animation
https://github.com/psyai-net/SelfTalk_release
공식 코드SelfTalk: A Self-Supervised Commutative Training Diagram to Comprehend 3D Talking Faces
https://github.com/pulkitag/ief
공식 코드https://github.com/puzzlepaint/camera_calibration
공식 코드Why Having 10,000 Parameters in Your Camera Model is Better Than Twelve
https://github.com/qhfang/accurateacl
공식 코드https://github.com/qingshi9974/BMVC2021-Hierarchical-Graph-Networks-for-3D-Human-Pose-Estimation
공식 코드https://github.com/qingshufan/GeneA-SLAM2
공식 코드https://github.com/qitaozhao/poseformerv2
공식 코드PoseFormerV2: Exploring Frequency Domain for Efficient and Robust 3D Human Pose Estimation
https://github.com/qiuyu96/codef
공식 코드CoDeF: Content Deformation Fields for Temporally Consistent Video Processing
https://github.com/qizhipei/fabind
공식 코드https://github.com/qq456cvb/3dcorrenhance
공식 코드Multiview Equivariance Improves 3D Correspondence Understanding with Minimal Feature Finetuning
https://github.com/qq456cvb/UKPGAN
공식 코드https://github.com/qq456cvb/cppf
공식 코드CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wild
https://github.com/qq456cvb/cppf2
공식 코드CPPF++: Uncertainty-Aware Sim2Real Object Pose Estimation by Vote Aggregation
https://github.com/qq456cvb/pace
공식 코드PACE: A Large-Scale Dataset with Pose Annotations in Cluttered Environments
https://github.com/qualityminds/cistgcn
공식 코드Context-based Interpretable Spatio-Temporal Graph Convolutional Network for Human Motion Forecasting
https://github.com/r-pad/se3_distributions
공식 코드Learning Orientation Distributions for Object Pose Estimation
https://github.com/r00tman/EventHands
공식 코드EventHands: Real-Time Neural 3D Hand Pose Estimation from an Event Stream
https://github.com/rafabs97/headpose_final
공식 코드RealHePoNet: a robust single-stage ConvNet for head pose estimation in the wild
https://github.com/rafaeelaudibert/FINNger
공식 코드FINNger -- Applying artificial intelligence to ease math learning for children
https://github.com/raivnlab/mimic
공식 코드https://github.com/raktimgg/robopepp
공식 코드https://github.com/raojiyong/ppap
공식 코드Probabilistic Prompt Distribution Learning for Animal Pose Estimation
https://github.com/rassaire/DmoGpm
공식 코드https://github.com/rawalkhirodkar/MIPNet
공식 코드Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation
https://github.com/rawalkhirodkar/car_pose
공식 코드Domain Randomization for Scene-Specific Car Detection and Pose Estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.