https://github.com/Multimodal3DVision/multimodal3dvision.github.io
Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose Estimation
Papers with Code 아카이브
Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 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/NU-LL/lighttrack-
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/NVIDIA/UnsupervisedLandmarkLearning
Unsupervised Part-Based Disentangling of Object Shape and Appearance
https://github.com/NVlabs/6dof-graspnet
6-DOF GraspNet: Variational Grasp Generation for Object Manipulation
https://github.com/NVlabs/PoseCNN-PyTorch
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
https://github.com/NVlabs/industreallib
https://github.com/NVlabs/latentfusion
https://github.com/Ne-ki-tos/Super_res
https://github.com/Neilblaze/Aerowave
https://github.com/Nhat-Thanh/ESPCN-Pytorch
https://github.com/Nhat-Thanh/ESPCN-TF
https://github.com/Nhat-Thanh/SRCNN-Pytorch
https://github.com/Nhat-Thanh/SRCNN-TF
https://github.com/Nhat-Thanh/VDSR-Pytorch
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
https://github.com/NieXC/pytorch-ppn
Generative Partition Networks for Multi-Person Pose Estimation
https://github.com/Nikhil619/Motion-direction-control-of-a-pi-robot-using-hand-movementss
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/NikhilBadami/YogiAI
Yoga-82: A New Dataset for Fine-grained Classification of Human Poses
https://github.com/NiravRaiyani/Mask-R-CNN-for-water-detection
https://github.com/NomiMalik0207/PedSynth-and-PedGNN-for-Pedestrian-Intention-Prediction
https://github.com/NonMagneticNeedle/vision.ai
https://github.com/Oishani/Machine-Learning-Projects
https://github.com/Okery/PyTorch-Simple-MaskRCNN
https://github.com/One-sixth/pixelshuffle_invert_pytorch
https://github.com/Oussamayousre/Yoga_pose_recognizer
OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/PINTO0309/HeadPoseEstimation-WHENet-yolov4-onnx-openvino
WHENet: Real-time Fine-Grained Estimation for Wide Range Head Pose
https://github.com/PJunhyuk/exercise-pose-analyzer
DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model
https://github.com/PJunhyuk/people-counting-pose
DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model
https://github.com/Pacific-cyber/KUKA_Catch_Project
SegICP: Integrated Deep Semantic Segmentation and Pose Estimation
https://github.com/PaddlePaddle/PaddleClas
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/PaddlePaddle/PaddleDetection
https://github.com/PaddlePaddle/PaddleSeg
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/model_zoo/recognition/stgcn.md
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/ParitoshParmar/MTL-AQA
Hierarchical NeuroSymbolic Approach for Comprehensive and Explainable Action Quality Assessment
https://github.com/Pea-Shooter/ADNet
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
https://github.com/PingoLH/CenterNet-HarDNet
https://github.com/Powercoder64/TAA-GCN
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.