Popular GitHub Repositories for Surface Normals

Official implementation of "Neuralangelo: High-Fidelity Neural Surface Reconstruction" (CVPR 2023)

? 目前最大的工业缺陷检测数据库及论文集 Constantly summarizing open source dataset and critical papers in the field of surface defect research which are of great importance.

[CVPR 2024] Official PyTorch implementation of SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering

[CVPR'22] ICON: Implicit Clothed humans Obtained from Normals

[Siggraph 2017] BundleFusion: Real-time Globally Consistent 3D Reconstruction using Online Surface Re-integration

CityGaussian Series for High-quality Large-Scale Scene Reconstruction with Gaussians

[CVPR 2023 Highlight] Neural Kernel Surface Reconstruction

[CVPR 2024 Oral] Rethinking Inductive Biases for Surface Normal Estimation

This repository contains the source codes for the paper "AtlasNet: A Papier-Maché Approach to Learning 3D Surface Generation ". The network is able to synthesize a mesh (point cloud + connectivity) from a low-resolution point cloud, or from an image.

Official implementation of the CVPR 2022 Paper "Neural RGB-D Surface Reconstruction"

A script for credentials-based attack surface enumeration and general reconnaissance of massive networks

[WACV'25 Oral] Fine-Tuning Image-Conditional Diffusion Models is Easier than You Think

Intrinsic3D - High-Quality 3D Reconstruction by Joint Appearance and Geometry Optimization with Spatially-Varying Lighting (ICCV 2017)

The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.

[Official Code] Pixel3DMM: Versatile Screen-Space Priors for Single-Image 3D Face Reconstruction

[CVPR 2021] SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration

This project proposes an end-to-end framework for semi-supervised Anomaly Detection and Segmentation in images based on Deep Learning.

The repository contains source code and models to use PixelNet architecture used for various pixel-level tasks. More details can be accessed at <http://www.cs.cmu.edu/~aayushb/pixelNet/>.

Stereo vision based object detection for ADAS, autonomous vehicle

[CVPR 2020] MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning