@inproceedings{6e1c520eac854ede9ed04fccbfe58669,
title = "Photo Filter Classification and Filter Recommendation without Much Manual Labeling",
abstract = "Because how users employ filters to photos may reveal user's preference or mental state, a photo filter classification method is potentially demanded to enable future large-scale analysis. We adopt the transfer learning technique to transform deep models pre-trained for object classification into models suitable for photo filter classification. Based on accurate classification results, we build a filter recommendation approach without much manual labeling. It can be easily extended when more training data are available. A series of experimental studies are conducted to demonstrate effectiveness of filter classification with transfer learning. We also demonstrate the proposed filter recommendation achieves encouraging performance.",
author = "Chu, {Wei Ta} and Fan, {Yu Tzu}",
year = "2019",
month = sep,
doi = "10.1109/MMSP.2019.8901831",
language = "English",
series = "IEEE 21st International Workshop on Multimedia Signal Processing, MMSP 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "IEEE 21st International Workshop on Multimedia Signal Processing, MMSP 2019",
address = "United States",
note = "21st IEEE International Workshop on Multimedia Signal Processing, MMSP 2019 ; Conference date: 27-09-2019 Through 29-09-2019",
}