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3D Human Pose Estimation

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하위 태스크: 9
평가표: 25
보존된 평가 기록: 447

3D Human Pose Estimation is a computer vision task that involves estimating the 3D positions and orientations of body joints and bones from 2D images or videos. The goal is to reconstruct the 3D pose of a person in real-time, which can be used in a variety of applications, such as virtual reality, human-computer interaction, and motion analysis.

코드

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

https://github.com/antoniolq/st-gcn

Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

https://github.com/anujdutt9/ESPCN

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

https://github.com/anuragmundhada/3dpose-demo-iitb

Learning 3D Human Pose from Structure and Motion

https://github.com/arjunarao619/SRCNN_Pytorch

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/arthur-qiu/freenoise-lavie

LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models

https://github.com/ataata107/Research-Papers-Implementations/tree/master/Single-shot%20multi%20person%203d%20body%20pose

Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB

https://github.com/atheesh1998/Image-Super-Resolution

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/atriumlts/subpixel

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

https://github.com/axinc-ai/ailia-models/tree/master/pose_estimation_3d/blazepose-fullbody

BlazePose: On-device Real-time Body Pose tracking

https://github.com/ayanglab/swinganmr

SwinIR: Image Restoration Using Swin Transformer

https://github.com/ayanglab/swinmr

SwinIR: Image Restoration Using Swin Transformer

https://github.com/baoshengyu/deep-high-resolution-net.pytorch

Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/bastianwandt/RepNet

RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation

https://github.com/bastianwandt/elepose

ElePose: Unsupervised 3D Human Pose Estimation by Predicting Camera Elevation and Learning Normalizing Flows on 2D Poses

https://github.com/bayuudachi/Real-esr-gan

Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

https://github.com/behnoudshafizadeh/ESPCN-SuperResolution-Tensorflow

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

https://github.com/bharat-b7/IPNet

Combining Implicit Function Learning and Parametric Models for 3D Human Reconstruction

https://github.com/bharat-b7/MultiGarmentNetwork

Multi-Garment Net: Learning to Dress 3D People from Images

https://github.com/blake58/openpose

Convolutional Pose Machines

https://github.com/boukhayma/3dhand

3D Hand Shape and Pose from Images in the Wild

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/cardboard-q/pifuhd_demo_model_test

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

https://github.com/cataai/posex

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

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

Convolutional Pose Machines

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

MogaNet: Multi-order Gated Aggregation 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/chenxuluo/OriNet-demo

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

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

Convolutional Pose Machines

https://github.com/chingswy/HumanPoseMemo

Learning from Synthetic Humans

https://github.com/chuanqichen/deepcoaching

DensePose: Dense Human Pose Estimation In The Wild

https://github.com/chuxiaoselena/SparsenessMeetsDeepness

Sparseness Meets Deepness: 3D Human Pose Estimation from Monocular Video

https://github.com/classner/up

Unite the People: Closing the Loop Between 3D and 2D Human Representations

https://github.com/cmbagent/cmbagent

AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

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