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lightfield botanist's Projects

gradsim icon gradsim

Differentiable simulation for system identification and visuomotor control

hashnerf-pytorch icon hashnerf-pytorch

Pure PyTorch Implementation of NVIDIA paper on Instant Training of Neural Graphics primitives: https://nvlabs.github.io/instant-ngp/

how_to_optimize_in_gpu icon how_to_optimize_in_gpu

This is a series of GPU optimization topics. Here we will introduce how to optimize the CUDA kernel in detail. I will introduce several basic kernel optimizations, including: elementwise, reduce, sgemv, sgemm, etc. The performance of these kernels is basically at or near the theoretical limit.

hyperreel icon hyperreel

Code release for HyperReel: High-Fidelity 6-DoF Video with Ray-Conditioned Sampling

image-to-image-translation icon image-to-image-translation

A Tensorflow implementation of the paper 'Image-to-Image Translation with Conditional Adversarial Nets' by Isola, et al.

imaginaire icon imaginaire

NVIDIA's Deep Imagination Team's PyTorch Library

immersive-ngp icon immersive-ngp

We present the first open-source VR NERF Unity package that brings high resolution, low-latency, 6-DOF NERF rendering to VR. This work is based on Nvidia's ground breaking instant-ngp technique.

jnerf icon jnerf

JNeRF is a NeRF benchmark based on Jittor. JNeRF re-implemented instant-ngp and achieved same performance with original paper.

juliengenovese icon juliengenovese

In this repository we have all the codes that we have developed

kaolin-wisp1 icon kaolin-wisp1

NVIDIA Kaolin Wisp is a PyTorch library powered by NVIDIA Kaolin Core to work with neural fields (including NeRFs, NGLOD, instant-ngp and VQAD).

keras-io icon keras-io

Keras documentation, hosted live at keras.io

langchain icon langchain

⚡ Building applications with LLMs through composability ⚡

latent-nerf icon latent-nerf

Official Implementation for "Latent-NeRF for Shape-Guided Generation of 3D Shapes and Textures"

learnopengl icon learnopengl

Code repository of all OpenGL chapters from the book and its accompanying website https://learnopengl.com

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