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Modeling the Forgetting Process using Image Regions
Aditya Khosla · Jianxiong Xiao · Antonio Torralba · Aude Oliva

Tue Dec 04 07:00 PM -- 12:00 AM (PST) @ Harrah’s Special Events Center 2nd Floor

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 over time 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 over time, 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.

Author Information

Aditya Khosla (MIT)
Jianxiong Xiao (Princeton University)
Antonio Torralba (Massachusetts Institute of Technology)
Aude Oliva (Massachusetts Institute of Technology)

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