Papers with Code 아카이브

3D Object Reconstruction

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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하위 태스크

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평가표

4

보존된 평가 기록

18

코드

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

https://github.com/laughtervv/tf_neural_renderer

Neural 3D Mesh Renderer

https://github.com/liuzhengzhe/ISS-Image-as-Stepping-Stone-for-Text-Guided-3D-Shape-Generation

3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction

https://github.com/liuzhengzhe/dreamstone-iss

3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction

https://github.com/mattiagaggi/3D-Pose-Estimator---MSc_project

Neural 3D Mesh Renderer

https://github.com/mees/self-supervised-3D

Self-supervised 3D Shape and Viewpoint Estimation from Single Images for Robotics

https://github.com/mikacuy/deformation_aware_embedding

Deformation-Aware 3D Model Embedding and Retrieval

https://github.com/natowi/3D-reconstruction-with-Neural-Networks

3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction

https://github.com/nywang16/Pixel2Mesh

Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images

https://github.com/oaeen/3D-point-cloud-generation

Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction

https://github.com/pranavbajoria93/3D_Reconstruction_3DR2N2

3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction

https://github.com/pravinthsam/Ilios-3D-model-generation

Dense 3D Object Reconstruction from a Single Depth View

https://github.com/qweas120/PSVH-3d-reconstruction

Deep Single-View 3D Object Reconstruction with Visual Hull Embedding

https://github.com/raphaelsulzer/dsr-benchmark

3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction

https://github.com/raphaelsulzer/dsrv-data

3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction

https://github.com/richardsfc/pixel2mesh-ssds

Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images

https://github.com/shunsukesaito/PIFu

PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization

https://github.com/tensorflow/models/tree/master/research/ptn

Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision

https://github.com/trailab/generalobjectmapping

Multi-view 3D Object Reconstruction and Uncertainty Modelling with Neural Shape Prior

https://github.com/ttaa9/genren

3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction

https://github.com/ventusff/neurecon

UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction

https://github.com/vnoves/aectech2019-sketchto3d-backend

Hierarchical Surface Prediction for 3D Object Reconstruction

https://github.com/wMito/HuSc3D

HuSc3D: Human Sculpture dataset for 3D object reconstruction

https://github.com/xhxuciedu/3DHand

Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images

https://github.com/xiaoqianruan1/partonomic_reconstruction

Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency

https://github.com/yongheng1991/3D-point-capsule-networks

3D Point Capsule Networks

https://github.com/yuzhenmao/MI_P2V

Pix2Vox++: Multi-scale Context-aware 3D Object Reconstruction from Single and Multiple Images

https://github.com/zerchen/AlignSDF

Grasping Field: Learning Implicit Representations for Human Grasps

https://github.com/zerchen/gSDF

Grasping Field: Learning Implicit Representations for Human Grasps

https://github.com/zxpzhong/3D-RecGAN-pytorch

3D Object Reconstruction from a Single Depth View with Adversarial Learning

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