Benchmark and resources for single super-resolution algorithms
A Caffe-based implementation of very deep convolution network for image super-resolution
torch implementation of srgan
A simple neural network implement in c++
Matlab reimplementation of SCNSR
A curated list of awesome computer vision resources
A curated list of deep learning resources for computer vision
caffe for transfer learning
Super Resolution for images using deep learning.
Image Super-Resolution for Anime-Style Art
A curated list of awesome Deep Learning tutorials, projects and communities.
92.45% on CIFAR-10 in Torch
Exercises for the Stanford/Coursera Machine Learning Class
waifu2x(original : https://github.com/nagadomi/waifu2x) re-implementation in C++ using OpenCV
Detectron2 is FAIR's next-generation research platform for object detection and segmentation.
subpixel: A subpixel convnet for super resolution with Tensorflow
SenseTime Research platform for single object tracking, implementing algorithms like SiamRPN and SiamMask.
Open MMLab Detection Toolbox with PyTorch
A Simple and Versatile Framework for Object Detection and Instance Recognition
A pedagogical implementation of Autograd
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
COCO API - Dataset @ http://cocodataset.org/
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Go, Javascript and more
A library containing both highly optimized building blocks and an execution engine for data pre-processing in deep learning applications
Configuration for Vim8
Dual Path Networks
Non-local Neural Networks for Video Classification
Deformable Convolutional Networks
An MXNet implementation of Mask R-CNN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Datasets, Transforms and Models specific to Computer Vision
Personal configurations.
Faster R-CNN, an MXNet implementation with distributed implementation and data parallelization.
Faster R-CNN
Feedforward style transfer
95.8% and 80% on CIFAR-10 and CIFAR-100
Determinantal point process
Deep Residual Learning for Image Recognition
500 Lines or Less
caffecn_master
Automatically exported from code.google.com/p/cuda-convnet2
Recurrent Neural Network - A curated list of resources dedicated to RNN
编程语言 | 排名 | 好于 | 星星数 |
---|---|---|---|
OpenEdge ABL | 3 | 98.87% | 64 |
Matlab | 10 | 99.84% | 258 |
Lua | 91 | 98.79% | 77 |
C++ | 913 | 98.50% | 77 |
Python | 4435 | 95.05% | 27 |