differentiable-rendering

A PyTorch Library for Accelerating 3D Deep Learning Research

Differentiable rendering without approximation.

Project page of paper "Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoning"

Point-NeRF: Point-based Neural Radiance Fields

3D mesh stylization driven by a text input in PyTorch

This repository contains the code for the CVPR 2020 paper "Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision"

A high-fidelity 3D face reconstruction library from monocular RGB image(s)

Project Page of 'GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction' [CVPR2019]

Differentiable Surface Splatting

SVG Differentiable Rendering: Generating vector graphics using neural networks. Support: text-to-SVG, Image-to-SVG, SVG Editing.

A differentiable 3D renderer with Pytorch, Tensorflow and Matlab interfaces

DIRT: a fast differentiable renderer for TensorFlow

A framework for 4D reconstruction from monocular videos.

[ECCV 2024 - ORAL] Official PyTorch implementation of Gaussian Frosting: Editable Complex Radiance Fields with Real-Time Rendering

Multi-View Mesh Reconstruction with Neural Deferred Shading (CVPR 2022)

Pytorch code for ICCV'23 paper. NEO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes

Auto-differentiable digitally reconstructed radiographs in PyTorch

Official Pytorch Implementation of 3DV2021 paper: SAFA: Structure Aware Face Animation.

[CVPR 2025] Official PyTorch implementation of MAtCha Gaussians: Atlas of Charts for High-Quality Geometry and Photorealism From Sparse Views

TensorFlow implementation of our CVPR 2021 Paper "Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes".