CVJul 10, 2019

Dunhuang Grottoes Painting Dataset and Benchmark

arXiv:1907.04589v214 citations
Originality Synthesis-oriented
AI Analysis

This addresses the need for digital methods in heritage preservation, but it is incremental as it introduces a new dataset rather than a novel method.

The authors tackled the problem of heritage protection and restoration by releasing the first public dataset for Dunhuang Grotto painting restoration, providing a large number of training and testing examples sufficient for deep learning approaches.

This document introduces the background and the usage of the Dunhuang Grottoes Dataset and the benchmark. The documentation first starts with the background of the Dunhuang Grotto, which is widely recognised as an priceless heritage. Given that digital method is the modern trend for heritage protection and restoration. Follow the trend, we release the first public dataset for Dunhuang Grotto Painting restoration. The rest of the documentation details the painting data generation. To enable a data driven fashion, this dataset provided a large number of training and testing example which is sufficient for a deep learning approach. The detailed usage of the dataset as well as the benchmark is described.

Foundations

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