Deep Learning

Frameworks for Neural Networks and Deep Learning.

Newest releases

extreme-assistant 2020-2021年计算机视觉综述论文分方向整理
 

PyTorchLightning Collection of tasks for fast prototyping, finetuning and solving applied deep learning problems.
 

cszn Blind Single Image Super-Resolution for Real Images
 

MariaEduardaDeAzevedo Este repositório contém um script em Python3 que reconhece se um rosto está ou não portando uma máscara!
 

lucidrains Implementation of Bottleneck Transformer, SotA visual recognition model with convolution + attention that outperforms EfficientNet and DeiT in terms of performance-computes trade-off, in Pytorch
 

chibohe text_recognition_toolbox: The reimplementation of a series of classical scene text recognition papers with Pytorch in a uniform way.
 

NVIDIA Pytorch implementation of our paper Hierarchical Multi-Scale Attention for Semantic Segmentation.
 

weecology Implementation of Hang et al. 2020 "Hyperspectral Image Classification with Attention Aided CNNs" for tree species prediction
 

VIDA-NYU AutoML Pipeline exploration tool compatible with Jupyter Notebooks. Supports auto-sklearn and D3M pipeline format.
 

gkeechin The fastest way to visualize GradCAM with your Keras models.
 

AlbertoSabater REPP is a learning based post-processing method to improve video object detections from any object detector. REPP links detections accross frames by evaluating their similarity and refines their classification and location to supp
 

nd7141 The code and data for the ICLR 2021 paper: Boost then Convolve: Gradient Boosting Meets Graph Neural Networks
 

tuvovan Keras Implementation of Vision Transformer (An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale)
 

xieenze This repository contains the data and code for "Trans2Seg: Transparent Object Segmentation with Transformer ".
 

silverbulletmdc This is the official implementation of article "Parsing-based viewaware embedding network for vehicle ReID"[arxiv], which has been accpeted by CVPR20 as a poster article.
 

microsoft An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
 

EmmaRocheteau This repository contains the code used for Predicting Patient Outcomes with Graph Representation Learning (https://arxiv.org/abs/2101.03940).
 

koyeongmin key points estimation and point instance segmentation approach for lane detection
 

tgc1997 A curated list of research papers in Video Captioning(from 2015 to 2020). Link to the code and project website if available.
 

sayakpaul This repository builds a product detection model to recognize products from grocery shelf images.
 

lucidrains Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)
 

lucidrains A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN
 

VITA-Group [ICLR 2021] "Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective" by Wuyang Chen, Xinyu Gong, Zhangyang Wang
 

Chen-Cai-OSU Paper list for equivariant neural network
 

daohu527 A curated list of all awesome things related to self-driving car.
 

naoto0804 Learning from Synthetic Shadows for Shadow Detection and Removal [Inoue+, IEEE TCSVT 2020].
 

ming71 CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Images
 

giannisnik Rep the Set: Neural Networks for Learning Set Representations
 

qq456cvb This repo is a TensorFlow implementation of our work UKPGAN. UKPGAN is an unsupervised 3D keypoint detector where keypoints are detected so that they could reconstruct the original object shape.
 

fgnt Convolutive Transfer Function Invariant SDR
 

SparkJiao This is the pytorch implementation of the long paper on ACL 2020: A Self-Training Method for Machine Reading Comprehension with Soft Evidence Extraction.
 

tiandunx This is the official implementation of our loss function search for face recognition. It's accepted by ICML 2020.
 

brendenpetersen Deep symbolic regression (DSR) is a deep learning algorithm for symbolic regression--the task of recovering tractable mathematical expressions from an input dataset. The package dsr contains the code for DSR, including a single-po