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blenderproc

A procedural Blender pipeline for photorealistic training image generation

cmake-examples

Useful CMake Examples

cnn-ps

deep-high-resolution-net.pytorch

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

deep-learning-papers-reading-roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

deep-near-light-photometric-stereo

This is the project page for our ECCV2020 paper: "Deep near-light photometric stereo for spatially varying reflectances".

deep-photometric-stereo-network

This is the project page for our ICCVW 2017 paper 'Deep photometric stereo network' by Hiroaki Santo, Masaki Samejima, Yusuke Sugano, Boxin Shi, and Yasuyuki Matsushita.

f2gan-few-shot-image-generation

Fusing-and-Filling GAN (F2GAN) for few-shot image generation, ACM MM2020

gps_net

libmtl

A PyTorch Library for Multi-Task Learning

light-structure-from-pin-motion

This is the project page for our IJCV paper 'Light structure from pin motion: Geometric point light source calibration' by Hiroaki Santo, Michael Waechter, Wen-Yan Lin, Yusuke Sugano, and Yasuyuki Matsushita (An earlier version was presented in ECCV 2018).

lofgan-pytorch

LoFGAN: Fusing Local Representations for Few-shot Image Generation. (ICCV 2021)

monocular-depth-estimation-toolbox

Monocular Depth Estimation Toolbox based on MMSegmentation.

near_ps

Code for solving photometric stereo under calibrated or semi-calibrated near point light source illumination (e.g., LEDs).

neuralps

Code of Neural Inverse Rendering for General Reflectance Photometric Stereo (ICML 2018)

normal_integration

Matlab codes for integrating the normal (gradient) field of a surface over a 2D grid

pcc_2e

Online resources for Python Crash Course (Second Edition), from No Starch Press

photometric-stereo

In this paper, we implement a standard photometric stereo algorithm. With the albedo being unknown and not constant for the images, this program takes multiple images and light source direction information as an input and produce the albedo map, surface normals map, heights map and 3d plot of the surface for provided input. All the images used in this project are provided in the homework assignment and stored in "src" folder. Several output plots shown in the work are stored in the "out" folder.

ps-fcn

Learning Based Calibrated Photometric Stereo for Non-Lambertian Surface (ECCV 2018)

pytorch-book

PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)

pytorch-cyclegan-and-pix2pix

Image-to-Image Translation in PyTorch

pytorch-lightning

The most intuitive, flexible, way for researchers, ML engineers and data scientists to build models (with PyTorch) and ML systems for the ML lifecycle with an obsessive focus on flexibility and performance.

sdps-net

Learning Based Uncalibrated Photometric Stereo for Non-Lambertian Surface (CVPR 2019)

simple-hrnet

Multi-person Human Pose Estimation with HRNet in Pytorch

surface_normal_uncertainty

(ICCV 2021 - oral) Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation

telecentric-calibration

unet-ps-4d

A UNet based network with 4D convolutions for photometric stereo which uses heat-maps for normal estimation