Papers with Code 아카이브
Pose Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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Pose prediction is to predict future poses given a window of previous poses.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/abhi1kumar/hrnet_pose_single_gpu
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/anilarmagan/HANDS19-Challenge-Toolbox
HOnnotate: A method for 3D Annotation of Hand and Object Poses
https://github.com/anshky/HR-NET
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/antheali/3dpartassembly
https://github.com/baoshengyu/deep-high-resolution-net.pytorch
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/boukhayma/3dhand
https://github.com/cataai/posex
Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction
https://github.com/code-implementation1/Code9/tree/main/hrnet
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/cvlab-epfl/single-stage-pose
https://github.com/d-shivam/Pose-estimation-based-action-recognition-for-help-Situation-Identification
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/deepmodeling/Uni-Mol
Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction
https://github.com/ducongju/HRNet
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/gox-ai/hrnet-pose-api
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/hz-ants/betapose
Estimating 6D Pose From Localizing Designated Surface Keypoints
https://github.com/hz-ants/obtain-an-object-mesh-and-create-labels
https://github.com/hz-ants/segmentation-driven-pose-train-
Estimating 6D Pose From Localizing Designated Surface Keypoints
https://github.com/hz-ants/yolo-6d
https://github.com/laowang666888/HRNET
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/mengyingfei/pose-3d-pytorch-ros
Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach
https://github.com/mikeshihyaolin/pose-hg-3d-preprocessing
Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach
https://github.com/nickgkan/3d_diffuser_actor
Act3D: 3D Feature Field Transformers for Multi-Task Robotic Manipulation
https://github.com/nish-97v/3D-human-pose-estimation
Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach
https://github.com/open-mmlab/mmpose
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/r-pad/taxpose
Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks
https://github.com/roboverseorg/roboverse
https://github.com/rongakowang/densemutualattention
HOnnotate: A method for 3D Annotation of Hand and Object Poses
https://github.com/sdll/hrnet-pose-estimation
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/shreyashampali/HOnnotate
HOnnotate: A method for 3D Annotation of Hand and Object Poses
https://github.com/shreyashampali/ho3d
HOnnotate: A method for 3D Annotation of Hand and Object Poses
https://github.com/sjtuytc/segmentation-driven-pose
Estimating 6D Pose From Localizing Designated Surface Keypoints
https://github.com/visionNoob/hrnet_pytorch
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/why2011btv/6d_pose_estimation
Estimating 6D Pose From Localizing Designated Surface Keypoints
https://github.com/wsjzha/deep-high-resolution-net.pytorch
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/xingyizhou/pytorch-pose-hg-3d
Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach
https://github.com/xn1997/HigherHRnet
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.