This is a dataset of corgi images scraped from the corgi subreddit. After filtering using an ImageNet classifier, the training set consists of 622,663 crops of 26,418 images.
This repository includes PyTorch Dataset implementations for downloading and using this dataset. The sole purpose of this dataset is to facilitate easier and faster fine-tuning of generative models to produce adorable corgis.
connect-caption-and-trace This repository contains the reference code for our paper Connecting What to Say With Where to Look by Modeling Human Attent
tsflex is a toolkit for flexible time series processing & feature extraction, that is efficient and makes few assumptions about sequence data. Useful
ISC-Track1-Submission The codes and related files to reproduce the results for Image Similarity Challenge Track 1. Required dependencies To begin with
SphereFace: Deep Hypersphere Embedding for Face Recognition By Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj and Le Song License SphereFa
ncnnqat ncnnqat is a quantize aware training package for NCNN on pytorch. Table of Contents ncnnqat Table of Contents Installation Usage Code Examples
AI Painting App We are making an app that will track our hand and helps us to draw from that. We will be using the advance knowledge of Machine Learni
VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation Created by Zeyu HU Introduction This work is based on our paper VMNet: Voxel-Mes
Tensorflow Implementation of "A ConvNet for the 2020s" This is the unofficial Tensorflow Implementation of ConvNeXt from "A ConvNet for the 2020s" pap
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation Created by Charles R. Qi, Hao Su, Kaichun Mo, Leonidas J. Guibas from Sta
Seeing Dynamic Scene in the Dark: High-Quality Video Dataset with Mechatronic Alignment This is a pytorch project for the paper Seeing Dynamic Scene i
PIXEL-LEVEL CRACK DETECTION FROM IMAGES OF LEVEE SYSTEMS : A COMPARATIVE STUDY G
human-pose-estimation-3d-python-cpp RealSenseD435 (RGB) 480x640 + CPU Corei9 45 FPS (Depth is not used) 1. Run 1-1. RealSenseD435 (RGB) 480x640 + CPU
ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search [paper] Introduction This is the official implementation of ViPNAS: Efficient V
Element selection for functional materials discovery by integrated machine learning of atomic contributions to properties 8.11.2021 Andrij Vasylenko I
Deep Learning for image classification pip install -r http://webia.lip6.fr/~baskiotisn/requirements-amal.txt Train an autoencoder python3 train_auto
Online Label Smoothing Pytorch implementation of Online Label Smoothing (OLS) presented in Delving Deep into Label Smoothing. Introduction As the abst
The purpose of this repo is to make it easy to get started with JAX. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I fou
Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN Official code for NeurIPS 2021 paper "Towards Scalable Unpaired Virtu
Lasagne Lasagne is a lightweight library to build and train neural networks in Theano. Its main features are: Supports feed-forward networks such as C
S-multi-SNE Supervised multi-SNE (S-multi-SNE): Multi-view visualisation and classification A repository containing the code to reproduce the findings
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