Papers with Code 아카이브

Pose Estimation

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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/fabio-sim/DeDoDe-ONNX-TensorRT

LoFTR: Detector-Free Local Feature Matching with Transformers

https://github.com/fabio-sim/LightGlue-ONNX

LightGlue: Local Feature Matching at Light Speed

https://github.com/facebookresearch/DensePose

DensePose: Dense Human Pose Estimation In The Wild

https://github.com/facebookresearch/DetectAndTrack

Detect-and-Track: Efficient Pose Estimation in Videos

https://github.com/facebookresearch/DomainBed

SVIRO: Synthetic Vehicle Interior Rear Seat Occupancy Dataset and Benchmark

https://github.com/facebookresearch/InterHand2.6M

InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose Estimation from a Single RGB Image

https://github.com/facebookresearch/SlowFast

Non-local Neural Networks

https://github.com/facebookresearch/detectron

https://github.com/facebookresearch/detectron2

https://github.com/facebookresearch/detectron2/tree/master/projects/DensePose/

DensePose: Dense Human Pose Estimation In The Wild

https://github.com/facebookresearch/maskrcnn-benchmark

https://github.com/facebookresearch/multiface

MeshTalk: 3D Face Animation from Speech using Cross-Modality Disentanglement

https://github.com/facebookresearch/mvdust3r

MV-DUSt3R+: Single-Stage Scene Reconstruction from Sparse Views In 2 Seconds

https://github.com/facebookresearch/posediffusion

PoseDiffusion: Solving Pose Estimation via Diffusion-aided Bundle Adjustment

https://github.com/facebookresearch/sapiens

Sapiens: Foundation for Human Vision Models

https://github.com/facebookresearch/xformers

Visual Attention Network

https://github.com/faheinrich/moon_pose_estimation_setup

Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image

https://github.com/faheinrich/moon_pose_with_detectron2

Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image

https://github.com/fandulu/Keras-for-Co-occurrence-Feature-Learning-from-Skeleton-Data-for-Action-Recognition

Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation

https://github.com/farrell236/SVRnet

Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry

https://github.com/fcr3/OpenVINO_Tutorials

Convolutional Pose Machines

https://github.com/fcr3/wine_detector

Convolutional Pose Machines

https://github.com/fdac18/ForensicImages

https://github.com/fdjingyuan/Deep-Fashion-Analysis-ECCV2018

Fashion Landmark Detection in the Wild

https://github.com/feicccccccc/Neural-ODE-Ex

Neural Ordinary Differential Equations

https://github.com/fenghansen/ESRGAN-Keras

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/fenglian425/Agriculture_AI

High-Resolution Representations for Labeling Pixels and Regions

https://github.com/fenglinglwb/MSPN

Rethinking on Multi-Stage Networks for Human Pose Estimation

https://github.com/fengwang/subpixel_conv2d

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

https://github.com/fengyidong123/openpose-master

Convolutional Pose Machines

https://github.com/ferseiti/reproducibility

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/final-0/Real-ESRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/final-0/Real-ESRGAN-bicubic

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/fiveai/saod

One Metric to Measure them All: Localisation Recall Precision (LRP) for Evaluating Visual Detection Tasks

https://github.com/flytocc/PaddleClas

Visual Attention Network

https://github.com/fourseaforfriend/waifu2x

Image Super-Resolution Using Deep Convolutional Networks

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