Jun 9, 2019 · We present a novel memory-augmented colorization model MemoPainter that can produce high-quality colorization with limited data.

Despite recent advancements in deep learning-based au- tomatic colorization, they are still limited when it comes to few-shot learning.

An unofficial implementation of MemoPainter(Coloring With Limited Data: Few-shot Colorization via Memory Augmented Networks) using PyTorch framework.

Despite recent advancements in deep learning-based au- tomatic colorization, they are still limited when it comes to few-shot learning.

Sep 8, 2024 · To tackle this issue, we present a novel memory-augmented colorization model MemoPainter that can produce high-quality colorization with limited ...

To tackle this issue, we present a novel memory-augmented colorization model MemoPainterunpaired that can produce high-quality colorization with limited data.

Yoo et al. [2] introduced memory enhancement module in GAN to solve the colorization problem under limited data. Recently, ChromaGAN [16] adopted the GAN ...

Despite recent advancements in deep learning-based automatic colorization, they are still limited when it comes to few-shot learning.

Coloring With Limited Data: Few-Shot Colorization via Memory Augmented Networks. 2019 | CONFERENCE DOI: 10.1109/CVPR.2019.01154.

We present an approach called Multi-ColorGAN based on memory-augmented networks for multi-color real vehicle coloring/generation with limited data.