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dr-benway's Projects

aelib icon aelib

Digital Assets for Houdini FX

colmap icon colmap

COLMAP - Structure-from-Motion and Multi-View Stereo

drit icon drit

Learning diverse image-to-image translation from unpaired data

drit_hr icon drit_hr

Multi-Modal Image-to-Image Translation on Tasks with High-Resolution Images

generateme icon generateme

Processing scripts used to generative glitch / art / design

gmic icon gmic

G'MIC is a full-featured open-source framework for image processing, providing several different user interfaces to convert/manipulate/filter/visualize generic image datasets, ranging from 1d scalar signals to 3d+t sequences of multi-spectral volumetric images, including 2d color images. http://gmic.eu

image-to-image-papers icon image-to-image-papers

🦓<->🦒 🌃<->🌆 A collection of image to image papers with code (constantly updating)

mops icon mops

Motion OPerators for Houdini, a motion graphics toolkit.

msgan icon msgan

MSGAN: Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis (CVPR2019)

negcut icon negcut

Official Implementation of Instance-wise Hard Negative Example Generation for Contrastive Learning in Unpaired Image-to-Image Translation (ICCV 2021)

neural_style_tf icon neural_style_tf

A Tensorflow implementation of neural style and related algorithms.

qlib icon qlib

A procedural asset library for SideFX Houdini. https://www.facebook.com/qLibHoudini

quickmocap-blenderaddon icon quickmocap-blenderaddon

Use this Blender Addon to import & clean Mocap Pose data from .npz or .pkl files. These files may have been created using Numpy, ROMP, or other motion capture processes that package their files accordingly.

revgan icon revgan

RevGAN implementation in PyTorch. We extend the Pix2pix and CycleGAN framework by exploring approximately invertible architectures in 2D and 3D. These architectures are approximately invertible by design and thus partially satisfy cycle-consistency before training even begins. Furthermore, since invertible architectures have constant memory complexity in depth, these models can be built arbitrarily deep without requiring additional memory. In the paper we demonstrate superior quantitative output on the Cityscapes and Maps datasets at near constant memory budget.

samplernn-pytorch icon samplernn-pytorch

PyTorch implementation of SampleRNN: An Unconditional End-to-End Neural Audio Generation Model

singlegan icon singlegan

SingleGAN: Image-to-Image Translation by a Single-Generator Network using Multiple Generative Adversarial Learning. ACCV 2018

ugatit icon ugatit

Official Tensorflow implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation

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