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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/bowu1004/instance_segmentation_RealSense

https://github.com/busyboxs/What-I-have-star

https://github.com/busyboxs/faster_rcnn_voc

https://github.com/bw2color/bw2color

XGBoost: A Scalable Tree Boosting System

https://github.com/cai-jianfeng/ROMP_mindspore

Monocular, One-stage, Regression of Multiple 3D People

https://github.com/caidao22/pkg-cams

Neural Ordinary Differential Equations

https://github.com/calipos/SuperGlue_NCNN

SuperGlue: Learning Feature Matching with Graph Neural Networks

https://github.com/caoquan95/6D-pose-project

PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

https://github.com/cardboard-q/pifuhd_demo_model_test

PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization

https://github.com/carpedm20/simulated-unsupervised-tensorflow

Learning from Simulated and Unsupervised Images through Adversarial Training

https://github.com/casia-iva-lab/zbs

Obj2Seq: Formatting Objects as Sequences with Class Prompt for Visual Tasks

https://github.com/casiopa/Madrid_Rooftops

https://github.com/cataai/posex

Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction

https://github.com/ccc013/DeepLearning_Notes

DeepFashion2: A Versatile Benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images

https://github.com/cersar/3D_detection

3D Bounding Box Estimation Using Deep Learning and Geometry

https://github.com/cgebbe/kaggle_pku-autonomous-driving

Objects as Points

https://github.com/chandyalex/Darkpose_Tensorflow

Distribution-Aware Coordinate Representation for Human Pose Estimation

https://github.com/changliu816/CV-paper-review

Non-local Neural Networks

https://github.com/chanyn/3Dpose_ssl

Convolutional Pose Machines

https://github.com/charlesYangM/py-faster-rcnn-80.28

https://github.com/charlesshang/fastmaskrcnn

https://github.com/chenchao15/2d_projection_matching

Unsupervised Learning of Shape and Pose with Differentiable Point Clouds

https://github.com/chengche6230/rest

Graph Neural Networks for Cross-Camera Data Association

https://github.com/chengguixiong1010/rnn_STAF_2dpose

Convolutional Pose Machines

https://github.com/chengjiali/DensePose3

DensePose: Dense Human Pose Estimation In The Wild

https://github.com/chengtan9907/simvpv2

Visual Attention Network

https://github.com/chenguolin/DiffSplat

SV3D: Novel Multi-view Synthesis and 3D Generation from a Single Image using Latent Video Diffusion

https://github.com/chengxuduan/advhmp

Learning Trajectory Dependencies for Human Motion Prediction

https://github.com/chenwuperth/ClaRAN

https://github.com/chenxuluo/OriNet-demo

OriNet: A Fully Convolutional Network for 3D Human Pose Estimation

https://github.com/chenyeheng/SmartCar

Fine-Grained Head Pose Estimation Without Keypoints

https://github.com/chenyeheng/SmartCar-FaceRec

Fine-Grained Head Pose Estimation Without Keypoints

https://github.com/chenyeheng/SmartCar-FaceRecognition

Fine-Grained Head Pose Estimation Without Keypoints

https://github.com/chenyouxin113/sota-status-investigation

Convolutional Pose Machines

https://github.com/chihyanghsu0805/object_detection_yolo

https://github.com/chingswy/HumanPoseMemo

Learning from Synthetic Humans

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