Papers with Code 아카이브

2D Pose Estimation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

2

평가표

9

보존된 평가 기록

21

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/kaviezhang/meshmamba

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

https://github.com/ken724049/action-recognition

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/khfs/DuplexMamba

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

https://github.com/kohillyang/mx-detection

OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/krishnac7/OpenPose

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/krutikabapat/Deep-Learning-based-OpenPose-Estimation

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/lab-emi/cleanumamba

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

https://github.com/laiviet/maml

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/laobaiswag/openpose1

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/laowang666888/HRNET

Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/learnables/learn2learn

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/leeyegy/SimDR

Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/leeyegy/simcc

Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/leopard-ai/betty

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/lgcollins/tr-maml

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/liang-faan/openpose

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/lif31up/model-agnostic-meta-learning

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/lif31up/prototypical-network

Prototypical Networks for Few-shot Learning

https://github.com/llan-ml/tesp

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/lmd0311/pointmamba

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

https://github.com/lncarter/Openpose

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/lwxGitHub123/openpose

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/lwxGitHub123/openpose20200610

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/mari-linhares/tensorflow-maml

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/mariehane/prototypical-networks

Prototypical Networks for Few-shot Learning

https://github.com/maxstrobel/HCN-PrototypeLoss-PyTorch

Prototypical Networks for Few-shot Learning

https://github.com/mengyingfei/pose-3d-pytorch-ros

Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach

https://github.com/mgolnezhad/openpose

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/mikehuisman/revisiting-learned-optimizers

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/mikeshihyaolin/pose-hg-3d-preprocessing

Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach

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/research/cv/ProtoNet

Prototypical Networks for Few-shot Learning

https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/attention/PolarizedSelfAttention.py

Polarized Self-Attention: Towards High-quality Pixel-wise Regression

https://github.com/mindspore-lab/mindone

Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/minseop-aitrics/FewshotLearning

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/mks0601/PoseFix_RELEASE

Deep High-Resolution Representation Learning for Human Pose Estimation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.