https://github.com/Ajithbalakrishnan/3D-Object-Reconstruction-from-Multi-View-Monocular-RGB-images
Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images
Papers with Code 아카이브
3D Reconstruction
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3D Reconstruction is the task of creating a 3D model or representation of an object or scene from 2D images or other data sources. The goal of 3D reconstruction is to create a virtual representation of an object or scene that can be used for a variety of purposes, such as visualization, animation, simulation, and analysis. It can be used in fields such as computer vision, robotics, and virtual reality.
Image: Gwak et al
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/AlgoHunt/Face-Xray
https://github.com/Amaranth819/3dr2n2-tensorflow
3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction
https://github.com/AndreeaDogaru/Gen3DSR
Gen3DSR: Generalizable 3D Scene Reconstruction via Divide and Conquer from a Single View
https://github.com/AndrewGavril/Kimera-VIO-RaspberryPi
Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping
https://github.com/ApdowJN/RTDense3DMapping
https://github.com/AshikaAnand12/FaceManipulation
DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection
https://github.com/Baukebrenninkmeijer/HackGAN
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/BiDAlab/DeepFakesON-Phys
DeepFakesON-Phys: DeepFakes Detection based on Heart Rate Estimation
https://github.com/CAVED123/TD-DPPO
Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning
https://github.com/CUHK-AIM-Group/LGS
Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgery
https://github.com/CatoGit/Comparing-the-Performance-of-Deepfake-Detection-Methods-on-Benchmark-Datasets
Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics
https://github.com/Chris10M/Ev2Hands
3D Pose Estimation of Two Interacting Hands from a Monocular Event Camera
https://github.com/ChrisWu1997/2D-Motion-Retargeting
Learning Character-Agnostic Motion for Motion Retargeting in 2D
https://github.com/ChrisWu1997/PQ-NET
https://github.com/CrisalixSA/h3ds
https://github.com/Daisy-Zhang/Face-X-ray
https://github.com/DataScienceNigeria/Fake-Detection-dataset-for-deepfake-from-Google-and-Jigsaw
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/DeepMotionEditing/deep-motion-editing
https://github.com/DreamTechAI/Direct3D
Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer
https://github.com/DreamTechAI/Direct3D-S2
Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention
https://github.com/EnvisageIITM/HoloJest
3D Shape Reconstruction from Sketches via Multi-view Convolutional Networks
https://github.com/FaceOnLive/DeepFake-Detection-SDK-Linux
https://github.com/Facebookresearch/deepsdf
DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
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/Gitikameher/Domain-Adaptive-Single-View-3D-Reconstruction
https://github.com/HKBU-HPML/IRS
https://github.com/HongguLiu/MesoNet.Pytorch
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
Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors
https://github.com/JiangWenPL/multiperson
Coherent Reconstruction of Multiple Humans from a Single Image
https://github.com/Jittor/JNeRF
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
https://github.com/JonasFrey96/Kimera-Semantics
Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping
https://github.com/JonathonLuiten/instant-nerf-pytorch
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
https://github.com/Kamysek/DeepLocalShapes
Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstruction
https://github.com/LONG-9621/Derivative_Efficient
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.