Python Cnns Resources

Explainable CNNs 📦 Flexible visualization package for generating layer-wise explanations for CNNs. It is a common notion that a Deep Learning model i

Attention Helps CNN See Better: Hybrid Image Quality Assessment Network [CVPRW 2022] Code for Hybrid Image Quality Assessment Network [paper] [code] T

CNNs fruits360 Train CNNs for the fruits360 data set in NTOU CS「Machine Vision」class. CNN on a pretrained model Build a CNN on a pretrained model, Res

TransFuse This repo holds the code of TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation Requirements Pytorch=1.6.0, 1.9.0 (=1.

CIFS This repository provides codes for CIFS (ICML 2021). CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Sel

Code for our ECCV paper What's the Point: Semantic Segmentation with Point Supervision. Summary This library is a custom build of Caffe for semantic i

inverse_attention This repository provides the official implementation of 'Learning to ignore: rethinking attention in CNNs' accepted in BMVC 2021. Le

GFNet-Pytorch (NeurIPS 2020) This repo contains the official code and pre-trained models for the glance and focus network (GFNet). Glance and Focus: a

Adversarial Robustness Comparison of Vision Transformer and MLP-Mixer to CNNs ArXiv Abstract Convolutional Neural Networks (CNNs) have become the de f

Deep3D: Automatic 2D-to-3D Video Conversion with CNNs How To Run To run this code. Please install MXNet following the official document. Deep3D requir

Tensorflow Programs and Tutorials This repository will contain Tensorflow tutorials on a lot of the most popular deep learning concepts. It'll also co

Coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Are Transformers More Robust Than CNNs? Pytorch implementation for NeurIPS 2021 Paper: Are Transformers More Robust Than CNNs? Our implementation is b

Torch-template-for-deep-learning Pytorch implementations of some **classical backbone CNNs, data enhancement, torch loss, attention, visualization and

hey-daug A light weight data augmentation tool for training CNNs and Viola Jones detectors (Haar Cascades). This tool inflates your data by up to six

Efficient networks for Computer Vision This repo contains source code of our work on designing efficient networks for different computer vision tasks:

Global Pooling, More than Meets the Eye: Position Information is Encoded Channel-Wise in CNNs, ICCV 2021 Global Pooling, More than Meets the Eye: Posi

Relation Classification via Multi-Level Attention CNNs It's a implement of this paper：Relation Classification via Multi-Level Attention CNNs. Training

Equivariant CNNs for the sphere and SO(3) implemented in PyTorch

News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which

VOneNet: CNNs with a Primary Visual Cortex Front-End A family of biologically-inspired Convolutional Neural Networks (CNNs). VOneNets have the followi

Is it Time to Replace CNNs with Transformers for Medical Images? Accepted at ICCV-2021: Workshop on Computer Vision for Automated Medical Diagnosis (C

CONetV2: Efficient Auto-Channel Size Optimization for CNNs Exciting News! CONetV2: Efficient Auto-Channel Size Optimization for CNNs has been accepted

DeepGCNs: Can GCNs Go as Deep as CNNs? In this work, we present new ways to successfully train very deep GCNs. We borrow concepts from CNNs, mainly re

GAN-image-detection This repository contains a GAN-generated image detector developed to distinguish real images from synthetic ones. The detector is

News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which

Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Comprehensive collection of Pixel Attribution methods for Computer Vision.

Introduction This is the implementation of Kim's Convolutional Neural Networks for Sentence Classification paper in PyTorch. Kim's implementation of t

Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Tested on many Common CNN Networks and Vision Transformers. ⭐ Includes smoo

Are Convolutional Neural Networks or Transformers more like human vision? This repository contains the code and fine-tuned models of popular Convoluti

Spherical CNNs Equivariant CNNs for the sphere and SO(3) implemented in PyTorch Overview This library contains a PyTorch implementation of the rotatio

Antialiased CNNs [Project Page] [Paper] [Talk] Making Convolutional Networks Shift-Invariant Again Richard Zhang. In ICML, 2019. Quick & easy start Ru

News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which