Python Improving-Adversarial-Transferability-of-Vision-Transformers Resources

Pytorch Implementation of Various Point Transformers Recently, various methods applied transformers to point clouds: PCT: Point Cloud Transformer (Men

Layered Neural Rendering in PyTorch This repository contains training code for the examples in the SIGGRAPH Asia 2020 paper "Layered Neural Rendering

NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination The offical implementation for the "NOH-NMS: Improving Pedestrian Detection by

OpenVINO Inference API This is a repository for an object detection inference API using the OpenVINO. It's supported on both Windows and Linux Operati

KoBART-Transformers SKT에서 공개한 KoBART를 편리하게 사용할 수 있게 transformers로 포팅하였습니다. Install (Optional) BartModel과 PreTrainedTokenizerFast를 이용하면 설치하실 필요 없습니다. p

Visual 3D Detection Package: This repo aims to provide flexible and reproducible visual 3D detection on KITTI dataset. We expect scripts starting from

NERDA Not only is NERDA a mesmerizing muppet-like character. NERDA is also a python package, that offers a slick easy-to-use interface for fine-tuning

SAINT-pytorch A Simple pyTorch implementation of "Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing" based on https://arx

🚀 Gated Graph Transformers Gated Graph Transformers for graph-level property prediction, i.e. graph classification and regression. Associated article

Recurrent VLN-BERT Code of the Recurrent-VLN-BERT paper: A Recurrent Vision-and-Language BERT for Navigation Yicong Hong, Qi Wu, Yuankai Qi, Cristian

Serpent.AI - Game Agent Framework (Python) Update: Revival (May 2020) Development work has resumed on the framework with the aim of bringing it into 2

NALP: Natural Adversarial Language Processing Welcome to NALP. Have you ever wanted to create natural text from raw sources? If yes, NALP is for you!

Accelerated deep learning R&D PyTorch framework for Deep Learning research and development. It focuses on reproducibility, rapid experimentation, and

pix2pix-keras Pix2pix implementation in keras. Original paper: Image-to-Image Translation with Conditional Adversarial Networks (pix2pix) Paper Author

Lightly is a computer vision framework for self-supervised learning. We, at Lightly, are passionate engineers who want to make deep learning more effi

Dream-Creator This project aims to simplify the process of creating a custom DeepDream model by using pretrained GoogleNet models and custom image dat

Build Type Linux MacOS Windows Build Status OpenPose has represented the first real-time multi-person system to jointly detect human body, hand, facia

neural-dream This is a PyTorch implementation of DeepDream. The code is based on neural-style-pt. Here we DeepDream a photograph of the Golden Gate Br

Detecto is a Python package that allows you to build fully-functioning computer vision and object detection models with just 5 lines of code. Inferenc

PyTorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision @misc{CV2018, author = {Donny You ([email protected])}, howpubl

Face Detection Docker Solution Using Faster R-CNN Dockerface is a deep learning face detector. It deploys a trained Faster R-CNN network on Caffe thro

About PCV PCV is a pure Python library for computer vision based on the book "Programming Computer Vision with Python" by Jan Erik Solem. More details

scikit-image: Image processing in Python Website (including documentation): https://scikit-image.org/ Mailing list: https://mail.python.org/mailman3/l

Serpent.AI - Game Agent Framework (Python) Update: Revival (May 2020) Development work has resumed on the framework with the aim of bringing it into 2

Caffe Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berke

SimpleCV Quick Links: About Installation [Docker] (#docker) Ubuntu Virtual Environment Arch Linux Fedora MacOS Windows Raspberry Pi SimpleCV Shell Vid

Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer