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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/IkeaASM/IKEA_ASM_Dataset

공식 코드

The IKEA ASM Dataset: Understanding People Assembling Furniture through Actions, Objects and Pose

https://github.com/InnovArul/vidreid_cosegmentation

공식 코드

Co-segmentation Inspired Attention Module for Video-based Computer Vision Tasks

https://github.com/IntelLabs/baa-ngp

공식 코드

BAA-NGP: Bundle-Adjusting Accelerated Neural Graphics Primitives

https://github.com/JaeYeonKang/STVUN-Pytorch

공식 코드

Deep Space-Time Video Upsampling Networks

https://github.com/JakubSochor/BoxCars

공식 코드

BoxCars: Improving Fine-Grained Recognition of Vehicles using 3-D Bounding Boxes in Traffic Surveillance

https://github.com/JanaldoChen/Anim-NeRF

공식 코드

Animatable Neural Radiance Fields from Monocular RGB Videos

https://github.com/Jeff-sjtu/HybrIK

공식 코드

HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimation

https://github.com/Jeff-sjtu/res-loglikelihood-regression

공식 코드

Human Pose Regression with Residual Log-likelihood Estimation

https://github.com/Jeff-sjtu/sampling-argmax

공식 코드

Localization with Sampling-Argmax

https://github.com/JiahuiYu/slimmable_networks

공식 코드

Slimmable Neural Networks

https://github.com/Jiaxin-Lu/ugg

공식 코드

UGG: Unified Generative Grasping

https://github.com/JihuaPeng/KTPFormer

공식 코드

KTPFormer: Kinematics and Trajectory Prior Knowledge-Enhanced Transformer for 3D Human Pose Estimation

https://github.com/JihyongOh/FISR

공식 코드

FISR: Deep Joint Frame Interpolation and Super-Resolution with a Multi-scale Temporal Loss

https://github.com/JimmySuen/integral-human-pose

공식 코드

Integral Human Pose Regression

https://github.com/JinluZhang1126/MixSTE

공식 코드

MixSTE: Seq2seq Mixed Spatio-Temporal Encoder for 3D Human Pose Estimation in Video

https://github.com/Johann-Huber/qd_grasp

공식 코드

Toward a Plug-and-Play Vision-Based Grasping Module for Robotics

https://github.com/Junggy/SCRREAM

공식 코드

SCRREAM : SCan, Register, REnder And Map:A Framework for Annotating Accurate and Dense 3D Indoor Scenes with a Benchmark

https://github.com/JunukCha/MultiPerson

공식 코드

Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement

https://github.com/Junyi42/geoaware-sc

공식 코드

Telling Left from Right: Identifying Geometry-Aware Semantic Correspondence

https://github.com/KHB1698/DC-GCT

공식 코드

Double-chain Constraints for 3D Human Pose Estimation in Images and Videos

https://github.com/KU-CVLAB/CoPoNeRF

공식 코드

Unifying Correspondence, Pose and NeRF for Pose-Free Novel View Synthesis from Stereo Pairs

https://github.com/KarenUllrich/pytorch-backprojection

공식 코드

Differentiable probabilistic models of scientific imaging with the Fourier slice theorem

https://github.com/Kartik-3004/facexformer

공식 코드

FaceXFormer: A Unified Transformer for Facial Analysis

https://github.com/KevinKecc/SRN

공식 코드

SRN: Side-output Residual Network for Object Reflection Symmetry Detection and Beyond

https://github.com/Khrylx/DLow

공식 코드

DLow: Diversifying Latent Flows for Diverse Human Motion Prediction

https://github.com/Khrylx/EgoPose

공식 코드

Ego-Pose Estimation and Forecasting as Real-Time PD Control

https://github.com/KieDani/SegformerPlusPlus

공식 코드

Segformer++: Efficient Token-Merging Strategies for High-Resolution Semantic Segmentation

https://github.com/KlabCMU/kin-poly

공식 코드

Dynamics-Regulated Kinematic Policy for Egocentric Pose Estimation

https://github.com/KochPJ/AutoPoseEstimation

공식 코드

Generating Annotated Training Data for 6D Object Pose Estimation in Operational Environments with Minimal User Interaction

https://github.com/KochPJ/vanishing-depth

공식 코드

Vanishing Depth: A Depth Adapter with Positional Depth Encoding for Generalized Image Encoders

https://github.com/KyungMinJin/OTPose

공식 코드

OTPose: Occlusion-Aware Transformer for Pose Estimation in Sparsely-Labeled Videos

https://github.com/LLNL/MuyGPyS

공식 코드

Light curve completion and forecasting using fast and scalable Gaussian processes (MuyGPs)

https://github.com/LUZW1998/CMFDUEI

공식 코드

An Effective Image Copy-Move Forgery Detection Using Entropy Information

https://github.com/Lakonik/MVEdit

공식 코드

Generic 3D Diffusion Adapter Using Controlled Multi-View Editing

https://github.com/LandskapeAI/triplet-attention

공식 코드

Rotate to Attend: Convolutional Triplet Attention Module

https://github.com/LinWeizheDragon/AutoFidgetDetection

공식 코드

Looking At The Body: Automatic Analysis of Body Gestures and Self-Adaptors in Psychological Distress

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