https://github.com/puhsu/point_clouds
Unsupervised Learning of Shape and Pose with Differentiable Point Clouds
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/pvdhove/owl-mask-rcnn
https://github.com/pwc-1/Paper-5/tree/main/mpt
MPT: Mesh Pre-Training with Transformers for Human Pose and Mesh Reconstruction
https://github.com/pwc-1/Paper-9/tree/main/2/mpt
MPT: Mesh Pre-Training with Transformers for Human Pose and Mesh Reconstruction
https://github.com/pwc-1/Paper-9/tree/main/4/pixelshuffle1d
https://github.com/pwc-1/Paper-9/tree/main/4/weakly-supervised
Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild
https://github.com/pwc-1/Paper-9/tree/main/5/van
https://github.com/pwc-1/Paper-9/tree/main/7/pixelshuffle1d
https://github.com/qdhill/openpose
https://github.com/qilei123/pyfasterrcnn
https://github.com/qingyun-wu/autogen-eval
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
https://github.com/qnqnckck/efficient-pose
https://github.com/qq330488563/TEST
https://github.com/quangvy2703/ABCNet-ESRGAN-SRTEXT
https://github.com/quic/aimet-model-zoo
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/quin-med-harvard-edu/kidney
https://github.com/quocdat32461997/Mask_RCNN
https://github.com/qweas120/PSVH-3d-reconstruction
Deep Single-View 3D Object Reconstruction with Visual Hull Embedding
https://github.com/r-pad/taxpose
TAX-Pose: Task-Specific Cross-Pose Estimation for Robot Manipulation
https://github.com/r-pad/zephyr
https://github.com/r06922019/butt_lion_paper_notes
https://github.com/radioactiverockets/OpenPoseBreackoutGame
https://github.com/rajahaseeb147/PCD_Registration_ReAgent
ReAgent: Point Cloud Registration using Imitation and Reinforcement Learning
https://github.com/rajatthepagal/DBPN-Keras
https://github.com/rajbharat/PoseNet-V2V-Pytorch1.0-Win10
https://github.com/rami0205/ngramswin
https://github.com/raunaks13/GeoNet-PyTorch
GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose
https://github.com/ravenwritingdesk/py-faster-rcnn-master
https://github.com/rayat137/Pose_3D
https://github.com/raymon-tian/hourglass-facekeypoints-detection
https://github.com/raymondyeh07/chirality_nets
3D human pose estimation in video with temporal convolutions and semi-supervised training
https://github.com/redrock303/HEMlets
HEMlets PoSh: Learning Part-Centric Heatmap Triplets for 3D Human Pose and Shape Estimation
https://github.com/renmengqisheng/stereo_multifisheye
ROVO: Robust Omnidirectional Visual Odometry for Wide-baseline Wide-FOV Camera Systems
https://github.com/renyang-home/ntire22_venh_sr
BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment
https://github.com/revanurambareesh/multiperson
Unsupervised Cross-Modal Alignment for Multi-Person 3D Pose Estimation
https://github.com/revygabor/WHENet
WHENet: Real-time Fine-Grained Estimation for Wide Range Head Pose
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.