natural image generation using ConvNets

Related tags

Deep Learningeyescream
Overview

The Eyescream Project

Generating Natural Images using Neural Networks.

For our research summary on this work, please read the Arxiv paper: http://arxiv.org/abs/1506.05751

For a high-level blog post with a live demo, please go to this website: http://soumith.ch/eyescream

This repository contains the code to train neural networks and reproduce our results from scratch.

Requirements

Eyescream requires or works with

  • Mac OS X or Linux
  • NVIDIA GPU with compute capability of 3.5 or above.

Installing Dependencies

  • Install Torch
  • Install the nngraph and tds packages:
luarocks install tds
luarocks install nngraph

Training your neural networks

  • If you want to train the CIFAR-10 image generators, read the README in the cifar/ folder
  • If you want to train the LSUN/Imagenet image generators, read the README in the lsun/ folder

Discuss the paper/code at

  • groups.google.com/forum/#!forum/torch7

See the CONTRIBUTING file for how to help out.

License

Eyescream is BSD-licensed. We also provide an additional patent grant.

Owner
Meta Archive
These projects have been archived and are generally unsupported, but are still available to view and use
Meta Archive
GitHub Repository
PyTorch implementation of Pay Attention to MLPs

gMLP PyTorch implementation of Pay Attention to MLPs. Quickstart Clone this repository. git clone https://github.com/jaketae/g-mlp.git Navigate to th

Jake Tae 34 Dec 13, 2022
Image Completion with Deep Learning in TensorFlow

Image Completion with Deep Learning in TensorFlow See my blog post for more details and usage instructions. This repository implements Raymond Yeh and

Brandon Amos 1.3k Dec 23, 2022
Code for "Diffusion is All You Need for Learning on Surfaces"

Source code for "Diffusion is All You Need for Learning on Surfaces", by Nicholas Sharp Souhaib Attaiki Keenan Crane Maks Ovsjanikov NOTE: the linked

Nick Sharp 247 Dec 28, 2022
Spatial Contrastive Learning for Few-Shot Classification (SCL)

This repo contains the official implementation of Spatial Contrastive Learning for Few-Shot Classification (SCL), which presents of a novel contrastive learning method applied to few-shot image class

Yassine 34 Dec 25, 2022
An open source machine learning library for performing regression tasks using RVM technique.

Introduction neonrvm is an open source machine learning library for performing regression tasks using RVM technique. It is written in C programming la

Siavash Eliasi 33 May 31, 2022
Repository for "Exploring Sparsity in Image Super-Resolution for Efficient Inference", CVPR 2021

SMSR Reposity for "Exploring Sparsity in Image Super-Resolution for Efficient Inference" [arXiv] Highlights Locate and skip redundant computation in S

Longguang Wang 225 Dec 26, 2022
Demonstration of transfer of knowledge and generalization with distillation

Distilling-the-Knowledge-in-a-Neural-Network This is an implementation of a part of the paper "Distilling the Knowledge in a Neural Network" (https://

26 Nov 25, 2022
Applying curriculum to meta-learning for few shot classification

Curriculum Meta-Learning for Few-shot Classification We propose an adaptation of the curriculum training framework, applicable to state-of-the-art met

Stergiadis Manos 3 Oct 25, 2022
用opencv的dnn模块做yolov5目标检测，包含C++和Python两个版本的程序

yolov5-dnn-cpp-py yolov5s,yolov5l,yolov5m,yolov5x的onnx文件在百度云盘下载， 链接：https://pan.baidu.com/s/1d67LUlOoPFQy0MV39gpJiw 提取码：bayj python版本的主程序是main_yolov5.

365 Jan 04, 2023
Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

Kai Zhang 2k Dec 31, 2022
PyTorch Implementation of Temporal Output Discrepancy for Active Learning, ICCV 2021

Temporal Output Discrepancy for Active Learning PyTorch implementation of Semi-Supervised Active Learning with Temporal Output Discrepancy, ICCV 2021.

Siyu Huang 33 Dec 06, 2022
Code for Motion Representations for Articulated Animation paper

Motion Representations for Articulated Animation This repository contains the source code for the CVPR'2021 paper Motion Representations for Articulat

Snap Research 851 Jan 09, 2023
Canonical Appearance Transformations

CAT-Net: Learning Canonical Appearance Transformations Code to accompany our paper "How to Train a CAT: Learning Canonical Appearance Transformations

STARS Laboratory 54 Dec 24, 2022
A lightweight deep network for fast and accurate optical flow estimation.

FastFlowNet: A Lightweight Network for Fast Optical Flow Estimation The official PyTorch implementation of FastFlowNet (ICRA 2021). Authors: Lingtong

Tone 161 Jan 03, 2023
Multi-modal co-attention for drug-target interaction annotation and Its Application to SARS-CoV-2

CoaDTI Multi-modal co-attention for drug-target interaction annotation and Its Application to SARS-CoV-2 Abstract Environment The test was conducted i

Layne_Huang 7 Nov 14, 2022
Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection

Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection (NimPme) The official implementation of Novel Instances Mining with

12 Sep 08, 2022
An end-to-end PyTorch framework for image and video classification

What's New: March 2021: Added RegNetZ models November 2020: Vision Transformers now available, with training recipes! 2020-11-20: Classy Vision v0.5 R

Facebook Research 1.5k Dec 31, 2022
BEAMetrics: Benchmark to Evaluate Automatic Metrics in Natural Language Generation

BEAMetrics: Benchmark to Evaluate Automatic Metrics in Natural Language Generation Installing The Dependencies $ conda create --name beametrics python

7 Jul 04, 2022
A simple root calculater for python

Root A simple root calculater Usage/Examples python3 root.py 9 3 4 # Order: number - grid - number of decimals # Output: 2.08

Reza Hosseinzadeh 5 Feb 10, 2022
The official implementation of CVPR 2021 Paper: Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation.

Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation This repository is the official implementation of CVPR 2021 paper:

9 Nov 14, 2022