https://gitlab.com/confidence_painting/cpaint
공식 코드Soft Expectation and Deep Maximization for Image Feature Detection
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://gitlab.com/retinai_sandro/glampoints
공식 코드https://huggingface.co/datasets/sankalpsinha77/MARVEL-40M
공식 코드MARVEL-40M+: Multi-Level Visual Elaboration for High-Fidelity Text-to-3D Content Creation
https://zenodo.org/record/12611978
공식 코드MMVR: Millimeter-wave Multi-View Radar Dataset and Benchmark for Indoor Perception
https://bitbucket.org/fafz/stein_particle_filter
Stein ICP for Uncertainty Estimation in Point Cloud Matching
https://gitee.com/gai-shaoyan/mind3d
Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry
https://github.com/000Justin000/torchdiffeq
https://github.com/07Agarg/Image-Resolution-Enhancement-SRCNN
https://github.com/0jason000/CLIFF
CLIFF: Carrying Location Information in Full Frames into Human Pose and Shape Estimation
https://github.com/1082-datascience/finalproject-finalproject-1082ds_group3
https://github.com/15517965908/keras-DBPN
https://github.com/163GitHub/AI
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/1716757342/mmsr
SymFormer: End-to-end symbolic regression using transformer-based architecture
https://github.com/1996scarlet/dense-head-pose-estimation
https://github.com/1adrianb/2D-and-3D-face-alignment
https://github.com/1adrianb/binary-face-alignment
https://github.com/1adrianb/binary-human-pose-estimation
https://github.com/1adrianb/face-alignment-training
https://github.com/1zgh/st-gcn
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/20151001860/Real_ESRGAN_paddle
Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
https://github.com/2023-MindSpore-1/ms-code-15/tree/main/dscnn
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/AlphaPose
AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/ArtTrack
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/adelaide_ea
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
https://github.com/2023-MindSpore-1/ms-code-162
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/2023-MindSpore-1/ms-code-199
https://github.com/2023-MindSpore-1/ms-code-201
https://github.com/2023-MindSpore-1/ms-code-207
https://github.com/2023-MindSpore-1/ms-code-208
https://github.com/2023-MindSpore-1/ms-code-210/tree/main/DBPN
https://github.com/2023-MindSpore-1/ms-code-210/tree/main/DDM
https://github.com/2023-MindSpore-1/ms-code-211/tree/main/detr
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/ESRGAN
Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HMR
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HRNetW48_seg
High-Resolution Representations for Labeling Pixels and Regions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.