PyTorch-Based Fast and Efficient Processing for Various Machine Learning Applications with Diverse Sparsity
-
Updated
Jul 13, 2026 - Cuda
PyTorch-Based Fast and Efficient Processing for Various Machine Learning Applications with Diverse Sparsity
Unofficial PyTorch implementation of the paper: "CenterNet3D: An Anchor free Object Detector for Autonomous Driving"
50%+ Faster Cylinder3D, compatible with current PyTorch, CUDA, and Spconv versions
Sparse ConvLSTM for Point Cloud Semantic Segmentation
spconv-Triton is a fast sparse convolution library with full operator support (SubM conv, Conv3D, Transposed Conv, Pooling). It is hardware-agnostic and runs on GPUs supporting Triton.
Sparse Autoencoder + Pruning for CMS jet classification | GSoC 2026 @ CERN-HSF | Built with spconv + PyTorch
Add a description, image, and links to the spconv topic page so that developers can more easily learn about it.
To associate your repository with the spconv topic, visit your repo's landing page and select "manage topics."