Papers with Code 아카이브
Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 31
- 보존된 평가 기록
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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/lwxGitHub123/openpose20200610
https://github.com/lye0618/torchdiffeq
https://github.com/lyp-deeplearning/awesome-retinal-registration
https://github.com/lyqcom/alphapose
https://github.com/lzccccc/3d-bounding-box-estimation-for-autonomous-driving
https://github.com/lzfff12/hfl-net
https://github.com/m-parchami/3DVehicleDetection
https://github.com/m-qiang/cortexode
https://github.com/machc/spherical_embeddings
https://github.com/mahmoudnafifi/11K-Hands
11K Hands: Gender recognition and biometric identification using a large dataset of hand images
https://github.com/mandubian/neural-ode
https://github.com/mandubian/pytorch-neural-ode
https://github.com/mansimane/WormML
Numerical Coordinate Regression with Convolutional Neural Networks
https://github.com/marciska/vpc-library
Visual Pursuit Control based on Gaussian Processes with Switched Motion Trajectories
https://github.com/maria-korosteleva/Body-Shape-Estimation
Detailed, accurate, human shape estimation from clothed 3D scan sequences
https://github.com/markmaxt/VideoSR
https://github.com/mathiasunberath/DeepDRR
X-ray-transform Invariant Anatomical Landmark Detection for Pelvic Trauma Surgery
https://github.com/mattiagaggi/3D-Pose-Estimator---MSc_project
Unsupervised Geometry-Aware Representation for 3D Human Pose Estimation
https://github.com/maudzung/CenterNet3D-PyTorch
https://github.com/maudzung/RTM3D
https://github.com/maudzung/SFA3D
https://github.com/maudzung/super-fast-accurate-3d-object-detection
https://github.com/max-andr/joint-cnn-mrf
Learning Human Pose Estimation Features with Convolutional Networks
https://github.com/maxfrei750/DeepParticleNet
https://github.com/maxfrei750/FibeR-CNN
https://github.com/maxstrobel/HCN-PrototypeLoss-PyTorch
https://github.com/mayank-17/Project-Image-Restoration-using-SRCNN
https://github.com/mayorquinmachines/YogAI
https://github.com/mdt48/semantic-segmentation-pytorch
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/med-seg/kidney
https://github.com/med-seg/kidney-mc
https://github.com/medchaabane/static_objects_geolocalization
End-to-end Learning Improves Static Object Geo-localization in Monocular Video
https://github.com/mediatek-neuropilot/mai22-real-time-video-sr
https://github.com/megapose6d/megapose6d
MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare
https://github.com/meghshukla/MPII-Human-Pose-Visualization
Bayesian Uncertainty and Expected Gradient Length -- Regression: Two Sides Of The Same Coin?
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.