https://github.com/megvii-research/basecls/tree/main/zoo/public/hrnet
Deep High-Resolution Representation Learning for Visual Recognition
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/megvii-research/conr
https://github.com/megvii-research/ijcai2023-conr
https://github.com/mehtadushy/SelecSLS-Pytorch
XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera
https://github.com/melgor/pyface
UMDFaces: An Annotated Face Dataset for Training Deep Networks
https://github.com/mengyingfei/pose-3d-pytorch-ros
Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach
https://github.com/metrics-lab/st-fmri
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/mgolnezhad/openpose
https://github.com/mhruz/POTR
https://github.com/mhw32/contrastive-ring-public
Conditional Negative Sampling for Contrastive Learning of Visual Representations
https://github.com/mialbro/PointFusion
PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation
https://github.com/mialbro/pytorch_pointfusion
PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation
https://github.com/miaohua1982/simple_fasterrcnn_pytorch
https://github.com/mic-dkfz/medicaldetectiontoolkit
https://github.com/michael13162/DoodleGAN
https://github.com/midas-research/text2facegan
Text2FaceGAN: Face Generation from Fine Grained Textual Descriptions
https://github.com/mikecheninoulu/Emotional-gesture-papers
https://github.com/mikeshihyaolin/pose-hg-3d-preprocessing
Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach
https://github.com/minar09/MGN
https://github.com/minar09/MGN-Py3
https://github.com/minar09/MultiGarmentNetworkPython3
https://github.com/mindspore-ai/contrib/tree/master/intern/pixelshuffle1d
https://github.com/mindspore-ai/models/blob/master/research/cv/StackedHourglass
https://github.com/mindspore-ai/models/blob/master/research/cv/simple_baselines/
https://github.com/mindspore-ai/models/tree/master/official/cv/maskrcnn
https://github.com/mindspore-ai/models/tree/master/official/cv/openpose
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/mindspore-ai/models/tree/master/official/cv/simple_pose
https://github.com/mindspore-ai/models/tree/master/official/cv/srcnn
https://github.com/mindspore-ai/models/tree/master/research/cv/AlphaPose
https://github.com/mindspore-ai/models/tree/master/research/cv/ArtTrack
https://github.com/mindspore-ai/models/tree/master/research/cv/ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/mindspore-ai/models/tree/master/research/cv/HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/mindspore-ai/models/tree/master/research/cv/PAMTRI
https://github.com/mindspore-ai/models/tree/master/research/cv/RefineNet
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
https://github.com/mindspore-ai/models/tree/master/research/cv/adelaide_ea
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
https://github.com/mindspore-ai/models/tree/master/research/cv/centernet_resnet50_v1
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.