537 Open source projects that are alternatives of or similar to Hzproc

Go package for computer vision using OpenCV 4 and beyond.

Tests and benchmarks for cudnn (and in the future, other nvidia libraries)

An implementation of the RoiAlign operation for Theano

Fast Point Cloud Segmentation Using Permutohedral Lattices

Cooperative primitives for CUDA C++.

Paperspace API for python

CUDA implementation of the 2D fast Poisson solver

Deformable ConvNets V2 (DCNv2) in PyTorch

Real-time video quality improvement for applications such as video-chat using Perceptual Losses

Clustering via Graphics Processor, using NVIDIA CUDA sdk to preform database clustering on the massively parallel graphics card processor

DES cracking using brute force algorithm and CUDA

Large octree map construction and rendering with CUDA and OpenGL

GraphVite: A General and High-performance Graph Embedding System

Tutorial for using Singularity containers

3D Spatial Transformer Network

Physically based renderer and simulation engine for real-time applications.

Fast Clojure Matrix Library

CARLsim is an efficient, easy-to-use, GPU-accelerated software framework for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail.

CUDA implementation of the Jacobi method

Use the Intel D435 real-sensing camera to realize target detection based on the Yolov3 framework under the Opencv DNN framework, and realize the 3D positioning of the Objection according to the depth information. Real-time display of the coordinates in the camera coordinate system.ADD--Using Yolov5 By TensorRT model,AGX-Xavier,RealTime Object Detection

R package for unleashing the power of NVIDIA GPU's

Torch7 bindings for cuda-convnet2 kernels!

Experiments with CUDA and Rust

label-smooth, amsoftmax, focal-loss, triplet-loss, lovasz-softmax. Maybe useful

Efficient GPU kernels for block-sparse matrix multiplication and convolution

Implementation of a simple CNN using CUDA

How fast can we brute force a 64-bit comparison?

Deep Learning Toolbox for Torch

Hornet data structure for sparse dynamic graphs and matrices

Image recognition and classification using Convolutional Neural Networks with TensorFlow

N body gravity attraction problem solver

A CUDA project for Molecular Dynamics, Brownian Dynamics, Hydrodynamics... intended to simulate a very generic system constructing a simulation with modules.

PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification (ICCV 2019) - Official PyTorch Implementation

Bregman ADMM for mass transportation on GPU

caffe implementation of "Arbitrary Style Transfer with Deep Feature Reshuffle"

Slides and demo code for past presentations

Superpixel SLIC for GPU (CUDA)

CUDA on Intel GPUs

A GPU implementation of smallpt (http://www.kevinbeason.com/smallpt/) with Bounding Volume Hierarchy (BVH) tree.

Atmospheric fluid dynamics solver optimized for GPUs.

an implementation of 3D Ken Burns Effect from a Single Image using PyTorch

an implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch

Deep Object Co-Segmentation

Performance-optimized wheels for TensorFlow (SSE, AVX, FMA, XLA, MPI)

Kernel Tuning Toolkit

source code for paper "Deep Discrete Supervised Hashing"

An GPU/CUDA implementation of the Hungarian algorithm

An interval arithmetic and affine arithmetic library for NVIDIA CUDA

A collection of Bash scripts and Dockerfiles to install data science Tool, Lib and application

Python interface to GPU-powered libraries

C++ Implementation of PyTorch Tutorials for Everyone

A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

This project is an old code for Chinese words split. It is written by CUDA at 2010, so it could not run well directly under you platform without an GPU card.

点云深度学习框架 | Point cloud Deep learning Framework

deformable_conv2d layer implemented in pytorch

Introduction to Parallel Programming class code

Qualia is a deep learning framework deeply integrated with automatic differentiation and dynamic graphing with CUDA acceleration. Qualia was built from scratch.