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PyTorch implementation of Contrastive Learning methods
High dynamic range (HDR) image viewer for graphics people
Visualizations for machine learning datasets
Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
A procedural Blender pipeline for photorealistic training image generation
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Easy-to-use glTF 2.0-compliant OpenGL renderer for visualization of 3D scenes.
A PyTorch Library for Accelerating 3D Deep Learning Research
[ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware
Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.
Image augmentation for machine learning experiments.
Project page of paper "Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoning"
Source code for pbrt, the renderer described in the third edition of "Physically Based Rendering: From Theory To Implementation", by Matt Pharr, Wenzel Jakob, and Greg Humphreys.
C++ implementation of the Python Numpy library
Convolutional Neural Network for 3D meshes in PyTorch
[CVPR'19] 3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans
TensorFlow Graphics: Differentiable Graphics Layers for TensorFlow
Code release for Local Light Field Fusion at SIGGRAPH 2019
Python implementation of A. Levin D. Lischinski and Y. Weiss. A Closed Form Solution to Natural Image Matting. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2006, New York
Real-time surfel-based mesh reconstruction from RGB-D video.
FML (Francis' Machine-Learnin' Library) - A collection of utilities for machine learning tasks
Latex code for making neural networks diagrams
Project Page of 'GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction' [CVPR2019]