A pytorch implementation of https://arxiv.org/abs/1704.03477
In order to draw other things than cats, you will find more drawing data here: https://github.com/googlecreativelab/quickdraw-dataset
epoch 1900:
epoch 2400:
epoch 3400
Default hyperparameters for training has been found here: https://github.com/tensorflow/magenta/blob/master/magenta/models/sketch_rnn/README.md
Human-Level Control through Deep Reinforcement Learning Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning. This imp
NerfingMVS Project Page | Paper | Video | Data NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo Yi Wei, Shaohui
PyTorch implementation of DAQ This is an official implementation of the paper "Distance-aware Quantization", accepted to ICCV2021. For more informatio
OREPA: Online Convolutional Re-parameterization This repo is the PyTorch implementation of our paper to appear in CVPR2022 on "Online Convolutional Re
DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a unified and state-of-the-art TensorFlow codebase for dense pixel labeling tasks.
BOVText: A Large-Scale, Bilingual Open World Dataset for Video Text Spotting Updated on December 10, 2021 (Release all dataset(2021 videos)) Updated o
Training data extraction from GPT-2 This repository contains code for extracting training data from GPT-2, following the approach outlined in the foll
ROS-UGV-Control-Interface Cam Closed: Cam Opened:
Alleviating Over-segmentation Errors by Detecting Action Boundaries Forked from ASRF offical code. This repo is the a implementation of replacing orig
Vector Quantization - Pytorch A vector quantization library originally transcribed from Deepmind's tensorflow implementation, made conveniently into a
Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V
deepface Deepface is a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for python. It is a hybrid
Distribution-Balanced Loss [Paper] The implementation of our paper Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets (
U-Net Implementation By Christopher Ley This is my interpretation and implementation of the famous paper "U-Net: Convolutional Networks for Biomedical
image-capture-class-annotation 領域を指定し、キーを入力することで画像を保存するツールです。 クラス分類用のデータセット作成を想定しています。 Requirement OpenCV 3.4.2 or later Usage 実行方法は以下です。 起動後はマウスクリック4
MUP for Haiku This is a (very preliminary) port of Yang and Hu et al.'s μP repo to Haiku and JAX. It's not feature complete, and I'm very open to sugg
Paddle-VisualAttention Results_Compared SVHN Dataset Methods Steps GPU Batch Size Learning Rate Patience Decay Step Decay Rate Training Speed (FPS) Ac
Attention-guided Temporal Coherent Video Object Matting This is the Github project for our paper Attention-guided Temporal Coherent Video Object Matti
SAT Style Augmented Translation Introduction By collecting high-quality data, we were able to train a model that outperforms Google Translate on 6 dif
PythonPID_Tuner Step 1: Takes a Process Reaction Curve in csv format - assumes data at 100ms interval (column names CV and PV) Step 2: Makes a rough e
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