LLM training in simple, raw C/CUDA

Instant neural graphics primitives: lightning fast NeRF and more

Code and data for paper "Deep Painterly Harmonization": https://arxiv.org/abs/1804.03189

DeepGEMM: clean and efficient FP8 GEMM kernels with fine-grained scaling

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

Squeeze-and-Excitation Networks

Fully Convolutional Instance-aware Semantic Segmentation

Efficient GPU kernels for block-sparse matrix multiplication and convolution

GA-Net: Guided Aggregation Net for End-to-end Stereo Matching

Code for KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs

PyTorch implementation of Deformable Convolution

Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade