Pytorch implementation from scratch of [Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization [Huang+, ICCV2017]]
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Updated
Jun 24, 2020 - Python
Pytorch implementation from scratch of [Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization [Huang+, ICCV2017]]
TensorFlow implementation of the paper "Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization" by Xun Huang and Serge Belongie
C++ implementation of neural networks library with Keras-like API. Contains majority of commonly used layers, losses and optimizers. Supports sequential and multi-input-output (flow) models. Supports single CPU, Multi-CPU and GPU tensor operations (using cuDNN and cuBLAS).
The re-implementation of style-based generator idea
PyTorch implementation of "Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization"
Implementation from scratch of [Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization [Huang+, ICCV2017]]
Artistic image style transfer implement in pytorch
Can we perform face hallucination using limited set of unaligned pairs?
the tensorflow implementation of adain:arbitrary image style transfer
Novel framework for Zero-Shot Style Alignment in Text-to-Image generation, incorporating Multi-Modal Context-Awareness and Multi-Reference Style Alignment, using minimal attention sharing, ensuring consistent style transfer without fine-tuning.
Neural Style transfer experiment with AdaIn operator : https://arxiv.org/abs/1703.06868
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
In this study, we work to transfer the pattern to the basic face image from the pattern face image, by adjusting the latent space and moving within it.
Interactive Style Transfer GUI - a system that pioneers the integration of neural style transfer with precise localization for a fully customizable artistic experience.
PyTorch Implementation of the paper "Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization"
Fast Cross-Domain Unsupervised Object detection through Online Style Transfer
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