cupy

NumPy & SciPy for GPU

Deep learning operations reinvented (for pytorch, tensorflow, jax and others)

A flexible framework of neural networks for deep learning

A simplified implemention of Faster R-CNN that replicate performance from origin paper

ChainerCV: a Library for Deep Learning in Computer Vision

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

TensorLy: Tensor Learning in Python.

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

Library for faster pinned CPU <-> GPU transfer in Pytorch

a reimplementation of PWC-Net in PyTorch that matches the official Caffe version

a reimplementation of LiteFlowNet in PyTorch that matches the official Caffe version

an implementation of softmax splatting for differentiable forward warping using PyTorch

CuPy fused PyTorch neural networks ops

A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python 🚀

Deep learning framework realized by Numpy purely, supports for both Dynamic Graph and Static Graph with GPU acceleration

Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset (CVPR'19)

A Simple & Flexible Cross Framework Operators Toolkit

Official source code for our paper "AdaCoF: Adaptive Collaboration of Flows for Video Frame Interpolation" (CVPR 2020)

A complete machine vision container that includes Jupyter notebooks with built-in code hinting, Anaconda, CUDA 11, TensorRT inference accelerator for Tensor cores, CuPy (GPU drop in replacement for Numpy), PyTorch, PyTorch geometric for Graph Neural Networks, TF2, Tensorboard, and OpenCV for accelerated workloads on NVIDIA Tensor cores and GPUs.

Chainer implementation of waifu2x