Memorability of image regions
Name
4570-memorability-of-image-regions.pdf
Description
Published version
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3.18 MB
Format
Adobe PDF
Checksum (MD5)
f9686b2b3ae28a55797bbd0f34d59935
Author(s) • • •
Khosla, Aditya
Xiao, Jianxiong
Torralba, Antonio
Oliva, Aude
Date Issued
2012
Journal
Advances in Neural Information Processing Systems
Citation
Khosla, Aditya, Jianxiong Xiao, Antonio Torralba, and Aude Oliva, "Memorability of image regions." Pereira, F., et al., eds., Advances in Neural Information Processing Systems 25 (San Diego, Calif.: Neural Information Processing Systems Foundation, Inc., 2012): url https://papers.nips.cc/paper/4570-memorability-of-image-regions ©2012 Author(s)
Version
Final published version
Abstract
While long term human visual memory can store a remarkable amount of visual information, it tends to degrade over time. Recent works have shown that image memorability is an intrinsic property of an image that can be reliably estimated using state-of-the-art image features and machine learning algorithms. However, the class of features and image information that is forgotten has not been explored yet. In this work, we propose a probabilistic framework that models how and which local regions from an image may be forgotten using a data-driven approach that combines local and global images features. The model automatically discovers memorability maps of individual images without any human annotation. We incorporate multiple image region attributes in our algorithm, leading to improved memorability prediction of images as compared to previous works. ©2012 Paper presented at the 26th Conference on Neural Information Processing Systems (NeurIPS 2012), Dec. 3-8, 2012, Lake Tahoe, Calif.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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Persistent DSpace Link
DOI of Published Version
https://papers.nips.cc/paper/4570-memorability-of-image-regions