A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers.

Last update: Dec 23, 2022

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Overview

ViTGAN: Training GANs with Vision Transformers

A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers.

Reference

Kwonjoon Lee, Huiwen Chang, Lu Jiang, Han Zhang, Zhuowen Tu, Ce Liu. ViTGAN: Training GANs with Vision Transformers. arXiv:2107.04589v1, 2021.

Author

Hong-Jia Chen

Owner

Hong-Jia Chen

Master student at National National Chung Cheng University, Taiwan. Study in Deep Learning and Computer Vision.

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A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers.

Related tags

Overview

ViTGAN: Training GANs with Vision Transformers

Reference

Author

Owner

Hong-Jia Chen

A check for whether the dependency jobs are all green.

Practical and Real-world applications of ML based on the homework of Hung-yi Lee Machine Learning Course 2021

SegTransVAE: Hybrid CNN - Transformer with Regularization for medical image segmentation

Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.

Implementation of "Distribution Alignment: A Unified Framework for Long-tail Visual Recognition"(CVPR 2021)

LightningFSL: Pytorch-Lightning implementations of Few-Shot Learning models.

Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction

Lane assist for ETS2, built with the ultra-fast-lane-detection model.

An efficient and easy-to-use deep learning model compression framework

Code for the paper "Combining Textual Features for the Detection of Hateful and Offensive Language"

Code of the paper "Multi-Task Meta-Learning Modification with Stochastic Approximation".

PyTorch implementation of Munchausen Reinforcement Learning based on DQN and SAC. Handles discrete and continuous action spaces

Python wrapper of LSODA (solving ODEs) which can be called from within numba functions.

Implementation detail for paper "Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet"

[v1 (ISBI'21) + v2] MedMNIST: A Large-Scale Lightweight Benchmark for 2D and 3D Biomedical Image Classification

Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.

An LSTM for time-series classification

[CVPR 2022] Structured Sparse R-CNN for Direct Scene Graph Generation

This program was designed to detect whether someone is wearing a facemask through a live video stream.

This repository includes the official project for the paper: TransMix: Attend to Mix for Vision Transformers.