Papers with Code 아카이브

3D Object Reconstruction

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

4

평가표

4

보존된 평가 기록

18

코드

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

https://github.com/vinairesearch/lemul

공식 코드

Toward Realistic Single-View 3D Object Reconstruction with Unsupervised Learning from Multiple Images

https://github.com/wagnew3/ARM

공식 코드

Amodal 3D Reconstruction for Robotic Manipulation via Stability and Connectivity

https://github.com/xcyan/nips16_PTN

공식 코드

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

https://github.com/xiexh20/CHORE

공식 코드

CHORE: Contact, Human and Object REconstruction from a single RGB image

https://github.com/xiexh20/behave-dataset

공식 코드

BEHAVE: Dataset and Method for Tracking Human Object Interactions

https://github.com/yhyang-myron/DreamComposer

공식 코드

DreamComposer: Controllable 3D Object Generation via Multi-View Conditions

https://github.com/za-cheng/PM-PMVS

공식 코드

Multi-view 3D Reconstruction of a Texture-less Smooth Surface of Unknown Generic Reflectance

https://github.com/zhengxi-git/phase-slam

공식 코드

Phase-SLAM: Phase Based Simultaneous Localization and Mapping for Mobile Structured Light Illumination Systems

https://github.com/zqyq/vtr

공식 코드

View Transformation Robustness for Multi-View 3D Object Reconstruction with Reconstruction Error-Guided View Selection

https://gitlab.com/hzxie/Pix2Vox

공식 코드

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

https://github.com/Ajithbalakrishnan/3D-Model-Reconstruction

Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images

https://github.com/Ajithbalakrishnan/3D-Object-Reconstruction-from-Multi-View-Monocular-RGB-images

Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images

https://github.com/Amaranth819/3dr2n2-tensorflow

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

https://github.com/CPUFronz/CapsVoxGAN

3D Point Capsule Networks

https://github.com/DreamTechAI/Direct3D-S2

Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention

https://github.com/Gitikameher/A-Point-Set-Generation-Network-for-3D-Object-Reconstruction-from-a-Single-Image

A Point Set Generation Network for 3D Object Reconstruction from a Single Image

https://github.com/JeremyFisher/deep_level_sets

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

https://github.com/JeremyFisher/few_shot_3dr

Matryoshka Networks: Predicting 3D Geometry via Nested Shape Layers

https://github.com/Radhika009/CMPE_295B_MASTERPROJECT

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

https://github.com/Wapity/Pixel2Mesh-Pytorch

Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images

https://github.com/Xharlie/ShapenetRender_more_variation

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

https://github.com/agnJason/RGB-D-PIFuHD

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

https://github.com/alexeybokhovkin/CAD-Deform

End-to-End CAD Model Retrieval and 9DoF Alignment in 3D Scans

https://github.com/bhiziroglu/3D-R2N2

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

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/charlesq34/pointnet-autoencoder

A Point Set Generation Network for 3D Object Reconstruction from a Single Image

https://github.com/chrischoy/3D-R2N2

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

https://github.com/col14m/cadrille

cadrille: Multi-modal CAD Reconstruction with Online Reinforcement Learning

https://github.com/dimtziwnas/InHandScanningICCV15_GroundTruthViewer

3D Object Reconstruction from Hand-Object Interactions

https://github.com/dimtziwnas/InHandScanningICCV15_HandMotionViewer

3D Object Reconstruction from Hand-Object Interactions

https://github.com/huochf/StackFLOW

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

https://github.com/justanhduc/graphx-conv

A Point Set Generation Network for 3D Object Reconstruction from a Single Image

https://github.com/kach/softraxterizer

Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoning

https://github.com/kingcheng2000/3D-point-cloud-generation

Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction

https://github.com/kingcheng2000/Multi-View-Silhouette-and-Depth-Decomposition-for-High-Resolution-3D-Object-Representation

Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation

https://github.com/kuangzijian/drifu-for-animals

ARCH: Animatable Reconstruction of Clothed Humans

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