Papers with Code 아카이브

3D Human Reconstruction

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하위 태스크

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평가표

10

보존된 평가 기록

54

코드

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

https://github.com/DonghwanKIM0101/MHCDIFF

공식 코드

Multi-hypotheses Conditioned Point Cloud Diffusion for 3D Human Reconstruction from Occluded Images

https://github.com/HZXu-526/Human-Avatar

공식 코드

Efficient Neural Implicit Representation for 3D Human Reconstruction

https://github.com/HongwenZhang/DaNet-DensePose2SMPL

공식 코드

Learning 3D Human Shape and Pose from Dense Body Parts

https://github.com/HongwenZhang/PyMAF

공식 코드

PyMAF: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop

https://github.com/IDEA-Research/OSX

공식 코드

One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformer

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

공식 코드

Animatable Neural Radiance Fields from Monocular RGB Videos

https://github.com/LizhenWangT/NormalGAN

공식 코드

NormalGAN: Learning Detailed 3D Human from a Single RGB-D Image

https://github.com/MoyGcc/vid2avatar

공식 코드

Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decomposition

https://github.com/QianliM/CAPE

공식 코드

Learning to Dress 3D People in Generative Clothing

https://github.com/SiTH-Diffusion/SiTH

공식 코드

SiTH: Single-view Textured Human Reconstruction with Image-Conditioned Diffusion

https://github.com/Skype-line/X-Avatar

공식 코드

X-Avatar: Expressive Human Avatars

https://github.com/Unity-Technologies/AnthroNet

공식 코드

AnthroNet: Conditional Generation of Humans via Anthropometrics

https://github.com/Unity-Technologies/com.unity.cv.synthetichumans

공식 코드

AnthroNet: Conditional Generation of Humans via Anthropometrics

https://github.com/YadiraF/PIXIE

공식 코드

Collaborative Regression of Expressive Bodies using Moderation

https://github.com/YuliangXiu/ECON

공식 코드

ECON: Explicit Clothed humans Optimized via Normal integration

https://github.com/ZhengZerong/DeepHuman

공식 코드

DeepHuman: 3D Human Reconstruction from a Single Image

https://github.com/ZhengZerong/PaMIR

공식 코드

PaMIR: Parametric Model-Conditioned Implicit Representation for Image-based Human Reconstruction

https://github.com/aigc3d/LHM

공식 코드

LHM: Large Animatable Human Reconstruction Model from a Single Image in Seconds

https://github.com/caizhongang/SMPLer-X

공식 코드

SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation

https://github.com/cure-lab/SmoothNet

공식 코드

SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos

https://github.com/diegothomas/TetraTSDF

공식 코드

TetraTSDF: 3D human reconstruction from a single image with a tetrahedral outer shell

https://github.com/dqj5182/contho_release

공식 코드

Joint Reconstruction of 3D Human and Object via Contact-Based Refinement Transformer

https://github.com/facebookresearch/AutoAvatar

공식 코드

AutoAvatar: Autoregressive Neural Fields for Dynamic Avatar Modeling

https://github.com/facebookresearch/KeypointNeRF

공식 코드

KeypointNeRF: Generalizing Image-based Volumetric Avatars using Relative Spatial Encoding of Keypoints

https://github.com/facebookresearch/frankmocap

공식 코드

FrankMocap: Fast Monocular 3D Hand and Body Motion Capture by Regression and Integration

https://github.com/facebookresearch/phosa

공식 코드

Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild

https://github.com/facebookresearch/pifuhd

공식 코드

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

https://github.com/google/nerfies

공식 코드

Nerfies: Deformable Neural Radiance Fields

https://github.com/hkust-vgd/rfnet-4d

공식 코드

RFNet-4D++: Joint Object Reconstruction and Flow Estimation from 4D Point Clouds with Cross-Attention Spatio-Temporal Features

https://github.com/jby1993/selfreconcode

공식 코드

SelfRecon: Self Reconstruction Your Digital Avatar from Monocular Video

https://github.com/jfzhang95/avatargen

공식 코드

AvatarGen: a 3D Generative Model for Animatable Human Avatars

https://github.com/marcopesavento/Super-resolution-3D-Human-Shape-from-a-Single-Low-Resolution-Image

공식 코드

Super-resolution 3D Human Shape from a Single Low-Resolution Image

https://github.com/mks0601/Hand4Whole_RELEASE

공식 코드

Accurate 3D Hand Pose Estimation for Whole-Body 3D Human Mesh Estimation

https://github.com/mks0601/I2L-MeshNet_RELEASE

공식 코드

I2L-MeshNet: Image-to-Lixel Prediction Network for Accurate 3D Human Pose and Mesh Estimation from a Single RGB Image

https://github.com/muelea/shapy

공식 코드

Accurate 3D Body Shape Regression using Metric and Semantic Attributes

https://github.com/naver/multi-hmr

공식 코드

Multi-HMR: Multi-Person Whole-Body Human Mesh Recovery in a Single Shot

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