Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included.

Overview

pixel_character_generator

Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included.

Dataset TinyHero

Dataset TinyHero includes 64x64 retro-pixel character. All characters were generated with Universal LPC spritesheet by makrohn. Each character in the dataset was randomly generated including: sex, body type, skin color and equipment with LPC spritesheet with 4 different angles view.

Image sixe Dataset size Source Download
64x64 3648 images LPC Spritesheet data.zip
912 per class

According to the rules of the LPC all art submissions were dual licensed under both GNU GPL 3.0 and CC-BY-SA 3.0. Further work produced in this repository is licensed under the same terms.

CC-BY-SA 3.0: http://creativecommons.org/licenses/by-sa/3.0/ See the file: cc-by-sa-3.0.txt

GNU GPL 3.0: http://www.gnu.org/licenses/gpl-3.0.html See the file: gpl-3.0.txt

Pixel Character Generator - DCGAN

Based on the DCGAN pytorch tutorial: https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html

Example results

Conditional DCGAN

Conditional DCGAN that generates a pixel character seen from selected angle.

  • different learning rate for discriminator and generator
  • soft labels
  • added classification loss to the discriminator. Discriminator have to guess fake/real but also the character angle
  • generator is conditioned with embedding from trainable look-up table that gives the info about the character view angle

DC Autoencoder

Deep convolutional autoencoder. This autoencoder have the same architecture as DCGAN above. The only difference is the additional fully-connected layer at the top of the encoder, which projects output from convolutional layer to selected latent size.

  • embedding size = 40 is enough for a good-quality reconstruction
  • autoencoder have great denoising properties
  • easier and more stable to train then GAN's

Owner
Agnieszka Mikołajczyk
Machine Learning Scientist & Enthusiast🤖 https://twitter.com/AgnMikolajczyk
Agnieszka Mikołajczyk
Interactive Terraform visualization. State and configuration explorer.

Rover - Terraform Visualizer Rover is a Terraform visualizer. In order to do this, Rover: generates a plan file and parses the configuration in the ro

Tu Nguyen 2.3k Jan 07, 2023
Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning, CVPR 2021

Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning By Zhenda Xie*, Yutong Lin*, Zheng Zhang, Yue Ca

Zhenda Xie 293 Dec 20, 2022
Individual Treatment Effect Estimation

CAPE Individual Treatment Effect Estimation Run CAPE python train_causal.py --loop 10 -m cape_cau -d NI --i_t 1 Run a baseline model python train_cau

S. Deng 4 Sep 02, 2022
Self-Supervised depth kalilia

Self-Supervised depth kalilia

24 Oct 15, 2022
💊 A 3D Generative Model for Structure-Based Drug Design (NeurIPS 2021)

A 3D Generative Model for Structure-Based Drug Design Coming soon... Citation @inproceedings{luo2021sbdd, title={A 3D Generative Model for Structu

Shitong Luo 118 Jan 05, 2023
Can we learn gradients by Hamiltonian Neural Networks?

Can we learn gradients by Hamiltonian Neural Networks? This project was carried out as part of the Optimization for Machine Learning course (CS-439) a

2 Aug 22, 2022
An implementation of the AdaOPS (Adaptive Online Packing-based Search), which is an online POMDP Solver used to solve problems defined with the POMDPs.jl generative interface.

AdaOPS An implementation of the AdaOPS (Adaptive Online Packing-guided Search), which is an online POMDP Solver used to solve problems defined with th

9 Oct 05, 2022
Official Repository for our ICCV2021 paper: Continual Learning on Noisy Data Streams via Self-Purified Replay

Continual Learning on Noisy Data Streams via Self-Purified Replay This repository contains the official PyTorch implementation for our ICCV2021 paper.

Jinseo Jeong 22 Nov 23, 2022
The source code for 'Noisy-Labeled NER with Confidence Estimation' accepted by NAACL 2021

Kun Liu*, Yao Fu*, Chuanqi Tan, Mosha Chen, Ningyu Zhang, Songfang Huang, Sheng Gao. Noisy-Labeled NER with Confidence Estimation. NAACL 2021. [arxiv]

30 Nov 12, 2022
👨‍💻 run nanosaur in simulation with Gazebo/Ingnition

🦕 👨‍💻 nanosaur_gazebo nanosaur The smallest NVIDIA Jetson dinosaur robot, open-source, fully 3D printable, based on ROS2 & Isaac ROS. Designed & ma

nanosaur 9 Jul 19, 2022
Cl datasets - PyTorch image dataloaders and utility functions to load datasets for supervised continual learning

Continual learning datasets Introduction This repository contains PyTorch image

berjaoui 5 Aug 28, 2022
Build a small, 3 domain internet using Github pages and Wikipedia and construct a crawler to crawl, render, and index.

TechSEO Crawler Build a small, 3 domain internet using Github pages and Wikipedia and construct a crawler to crawl, render, and index. Play with the r

JR Oakes 57 Nov 24, 2022
A disassembler for the RP2040 Programmable I/O State-machine!

piodisasm A disassembler for the RP2040 Programmable I/O State-machine! Usage Just run piodisasm.py on a file that contains the PIO code as hex! (Such

Ghidra Ninja 29 Dec 06, 2022
MonoScene: Monocular 3D Semantic Scene Completion

MonoScene: Monocular 3D Semantic Scene Completion MonoScene: Monocular 3D Semantic Scene Completion] [arXiv + supp] | [Project page] Anh-Quan Cao, Rao

298 Jan 08, 2023
Real-Time High-Resolution Background Matting

Real-Time High-Resolution Background Matting Official repository for the paper Real-Time High-Resolution Background Matting. Our model requires captur

Peter Lin 6.1k Jan 03, 2023
Simulation-based inference for the Galactic Center Excess

Simulation-based inference for the Galactic Center Excess Siddharth Mishra-Sharma and Kyle Cranmer Abstract The nature of the Fermi gamma-ray Galactic

Siddharth Mishra-Sharma 3 Jan 21, 2022
Code for Fold2Seq paper from ICML 2021

[ICML2021] Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design Environment file: environment.yml Data and Feat

International Business Machines 43 Dec 04, 2022
An improvement of FasterGICP: Acceptance-rejection Sampling based 3D Lidar Odometry

fasterGICP This package is an improvement of fast_gicp Please cite our paper if possible. W. Jikai, M. Xu, F. Farzin, D. Dai and Z. Chen, "FasterGICP:

79 Dec 31, 2022
Some pre-commit hooks for OpenMMLab projects

pre-commit-hooks Some pre-commit hooks for OpenMMLab projects. Using pre-commit-hooks with pre-commit Add this to your .pre-commit-config.yaml - rep

OpenMMLab 16 Nov 29, 2022
Language models are open knowledge graphs ( non official implementation )

language-models-are-knowledge-graphs-pytorch Language models are open knowledge graphs ( work in progress ) A non official reimplementation of Languag

theblackcat102 132 Dec 18, 2022