TY - GEN
T1 - What Makes an Object Memorable?
AU - Dubey, Rachit
AU - Peterson, Joshua
AU - Khosla, Aditya
AU - Yang, Ming-Hsuan
AU - Ghanem, Bernard
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2016/2/19
Y1 - 2016/2/19
N2 - Recent studies on image memorability have shed light on what distinguishes the memorability of different images and the intrinsic and extrinsic properties that make those images memorable. However, a clear understanding of the memorability of specific objects inside an image remains elusive. In this paper, we provide the first attempt to answer the question: what exactly is remembered about an image? We augment both the images and object segmentations from the PASCAL-S dataset with ground truth memorability scores and shed light on the various factors and properties that make an object memorable (or forgettable) to humans. We analyze various visual factors that may influence object memorability (e.g. color, visual saliency, and object categories). We also study the correlation between object and image memorability and find that image memorability is greatly affected by the memorability of its most memorable object. Lastly, we explore the effectiveness of deep learning and other computational approaches in predicting object memorability in images. Our efforts offer a deeper understanding of memorability in general thereby opening up avenues for a wide variety of applications. © 2015 IEEE.
AB - Recent studies on image memorability have shed light on what distinguishes the memorability of different images and the intrinsic and extrinsic properties that make those images memorable. However, a clear understanding of the memorability of specific objects inside an image remains elusive. In this paper, we provide the first attempt to answer the question: what exactly is remembered about an image? We augment both the images and object segmentations from the PASCAL-S dataset with ground truth memorability scores and shed light on the various factors and properties that make an object memorable (or forgettable) to humans. We analyze various visual factors that may influence object memorability (e.g. color, visual saliency, and object categories). We also study the correlation between object and image memorability and find that image memorability is greatly affected by the memorability of its most memorable object. Lastly, we explore the effectiveness of deep learning and other computational approaches in predicting object memorability in images. Our efforts offer a deeper understanding of memorability in general thereby opening up avenues for a wide variety of applications. © 2015 IEEE.
UR - http://hdl.handle.net/10754/621295
UR - https://ivul.kaust.edu.sa/Documents/Publications/2015/What%20makes%20an%20object%20memorable.pdf
UR - http://www.scopus.com/inward/record.url?scp=84973923101&partnerID=8YFLogxK
U2 - 10.1109/ICCV.2015.130
DO - 10.1109/ICCV.2015.130
M3 - Conference contribution
SN - 9781467383912
SP - 1089
EP - 1097
BT - 2015 IEEE International Conference on Computer Vision (ICCV)
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -