serereuk's repositories
Voice_Converter_CycleGAN
Voice Converter Using CycleGAN and Non-Parallel Data
rainbow-is-all-you-need
Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners with Latest APIs
awesome-anomaly-detection
A curated list of awesome anomaly detection resources
darknet
YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )
data-augmentation-review
List of useful data augmentation resources. You will find here some not common techniques, libraries, links to github repos, papers and others.
datasets
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
deep-learning-project-template
Pytorch Lightning code guideline for conferences
docker-python
Kaggle Python docker image
FastCampus
Subset of FastCampus Lecture Code (Data Analysis A to Z)
Learning-Texture-Invariant-Representation
Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation, CVPR 2020
maskrcnn-benchmark
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
pba
Efficient Learning of Augmentation Policy Schedules
PS-KD-Pytorch
Official PyTorch implementation of PS-KD
relu_networks_overconfident
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem [CVPR 2019, oral]
Sculpture-GAN
3D-DCGAN trained on a corpus of 3D printable objects - as a result, the generations are usually 3D printable
serereuk.github.io
💎 🐳 A super customizable Jekyll theme for personal site, team site, blog, project, documentation, etc.
ss-ood
Self-Supervised Learning for OOD Detection (NeurIPS 2019)
Tobigo_renewal
New version for Tobigo
UniTrack
Unified tracking framework with a single appearance model. It supports Single Object Tracking (SOT), Video Object Segmentation (VOS), Multi-Object Tracking (MOT), Multi-Object Tracking and Segmentation (MOTS), Pose Tracking, Video Instance Segmentation (VIS), and class-agnostic MOT (e.g. TAO dataset).