Isola, P.[Phillip],
Xiao, J.X.[Jian-Xiong],
Parikh, D.,
Torralba, A.B.[Antonio B.],
Oliva, A.[Aude],
What Makes a Photograph Memorable?,
PAMI(36), No. 7, July 2014, pp. 1469-1482.
IEEE DOI
1407
BibRef
Earlier: A1, A2, A4, A5, Only:
What makes an image memorable?,
CVPR11(145-152).
IEEE DOI
1106
What are the properties? Learn what are the features based on dataset
analysis. Prediction is easier than creation.
BibRef
Han, J.,
Chen, C.,
Shao, L.,
Hu, X.,
Han, J.,
Liu, T.,
Learning Computational Models of Video Memorability from fMRI Brain
Imaging,
Cyber(45), No. 8, August 2015, pp. 1692-1703.
IEEE DOI
1506
Brain models
BibRef
Fei, M.J.[Meng-Juan],
Jiang, W.[Wei],
Mao, W.J.[Wei-Jie],
Memorable and rich video summarization,
JVCIR(42), No. 1, 2017, pp. 207-217.
Elsevier DOI
1701
Key frame
BibRef
Jing, P.G.[Pei-Guang],
Su, Y.T.[Yu-Ting],
Nie, L.Q.[Li-Qiang],
Gu, H.M.[Hui-Min],
Predicting Image Memorability Through Adaptive Transfer Learning From
External Sources,
MultMed(19), No. 5, May 2017, pp. 1050-1062.
IEEE DOI
1704
Adaptation models
BibRef
Lahrache, S.[Souad],
El-Ouazzani, R.[Rajae],
El-Qadi, A.[Abderrahim],
Rules of photography for image memorability analysis,
IET-IPR(12), No. 7, July 2018, pp. 1228-1236.
DOI Link
1806
BibRef
Khanna, M.T.[Meera Thapar],
Ralekar, C.[Chetan],
Goel, A.[Anurika],
Chaudhury, S.[Santanu],
Lall, B.[Brejesh],
Memorability-based image compression,
IET-IPR(13), No. 9, 18 July 2019, pp. 1490-1501.
DOI Link
1907
Memorability of an image, as a perceptual measure while image coding.
BibRef
Jing, P.G.[Pei-Guang],
Su, Y.T.[Yu-Ting],
Nie, L.Q.[Li-Qiang],
Gu, H.M.[Hui-Min],
Liu, J.[Jing],
Wang, M.[Meng],
A Framework of Joint Low-Rank and Sparse Regression for Image
Memorability Prediction,
CirSysVideo(29), No. 5, May 2019, pp. 1296-1309.
IEEE DOI
1905
Jointly learn a low-rank projection matrix that enables us to
decompose the original data into a component part and an error part
and a sparse regression coefficient vector for image memorability
prediction.
Sparse matrices, Visualization, Robustness, Matrix decomposition,
Task analysis, Approximation algorithms, Heuristic algorithms,
subspace learning
BibRef
Basavaraju, S.[Sathisha],
Gaj, S.[Sibaji],
Sur, A.[Arijit],
Object Memorability Prediction using Deep Learning:
Location and Size Bias,
JVCIR(59), 2019, pp. 117-127.
Elsevier DOI
1903
Object Memorability, Deep Learning, Transfer Learning
BibRef
Lu, J.X.[Jia-Xin],
Xu, M.[Mai],
Yang, R.[Ren],
Wang, Z.L.[Zu-Lin],
Understanding and Predicting the Memorability of Outdoor Natural
Scenes,
IP(29), 2020, pp. 4927-4941.
IEEE DOI
2003
Databases, Predictive models, Visualization, Analytical models, Face,
Feature extraction, Correlation, Memorability.
BibRef
Jing, P.G.[Pei-Guang],
Shang, Y.C.[Yue-Chen],
Nie, L.Q.[Li-Qiang],
Su, Y.T.[Yu-Ting],
Liu, J.[Jing],
Wang, M.[Meng],
Learning Low-Rank Sparse Representations With Robust Relationship
Inference for Image Memorability Prediction,
MultMed(23), 2021, pp. 2259-2272.
IEEE DOI
2108
Visualization, Robustness, Sparse matrices, Correlation,
Predictive models, Task analysis, Adaptation models, relationship structure
See also Low-Rank Regularized Multi-Representation Learning for Fashion Compatibility Prediction.
BibRef
Yuan, X.T.[Xiao-Tong],
Liu, X.,
Yan, S.C.[Shui-Cheng],
Visual Classification With Multitask Joint Sparse Representation,
IP(21), No. 10, October 2012, pp. 4349-4360.
IEEE DOI
1209
BibRef
Earlier: A1, A3, Only:
CVPR10(3493-3500).
IEEE DOI Video of talk:
WWW Link.
1006
BibRef
Yuan, X.T.[Xiao-Tong],
Yan, S.C.[Shui-Cheng],
Forward Basis Selection for Pursuing Sparse Representations over a
Dictionary,
PAMI(35), No. 12, 2013, pp. 3025-3036.
IEEE DOI
1311
Dictionaries
BibRef
Zhang, Z.[Zhao],
Li, F.Z.[Fan-Zhang],
Zhao, M.B.[Ming-Bo],
Zhang, L.[Li],
Yan, S.C.[Shui-Cheng],
Joint Low-Rank and Sparse Principal Feature Coding for Enhanced
Robust Representation and Visual Classification,
IP(25), No. 6, June 2016, pp. 2429-2443.
IEEE DOI
1605
image classification
BibRef
Wang, L.[Lei],
Zhang, Z.[Zhao],
Liu, G.C.[Guang-Can],
Ye, Q.L.[Qiao-Lin],
Qin, J.[Jie],
Wang, M.[Meng],
Robust Adaptive Low-Rank and Sparse Embedding for Feature
Representation,
ICPR18(800-805)
IEEE DOI
1812
Feature extraction, Data mining, Encoding, Optimization,
Principal component analysis, Linear programming,
classification
BibRef
Zhang, Z.[Zhao],
Li, F.Z.[Fan-Zhang],
Zhao, M.B.[Ming-Bo],
Zhang, L.[Li],
Yan, S.C.[Shui-Cheng],
Robust Neighborhood Preserving Projection by Nuclear/L2,1-Norm
Regularization for Image Feature Extraction,
IP(26), No. 4, April 2017, pp. 1607-1622.
IEEE DOI
1704
feature extraction
BibRef
Ren, J.H.[Jia-Huan],
Zhang, Z.[Zhao],
Li, S.[Sheng],
Liu, G.C.[Guang-Can],
Wang, M.[Meng],
Yan, S.C.[Shui-Cheng],
Robust Projective Low-Rank and Sparse Representation by Robust
Dictionary Learning,
ICPR18(1851-1856)
IEEE DOI
1812
Machine learning, Dictionaries, Feature extraction,
Sparse matrices, Encoding, Optimization, Training data,
robust matrix factorization
BibRef
Lu, W.[Wei],
Zhai, Y.[Yujia],
Han, J.[Jiaze],
Jing, P.G.[Pei-Guang],
Liu, Y.[Yu],
Su, Y.T.[Yu-Ting],
VMemNet: A Deep Collaborative Spatial-Temporal Network With Attention
Representation for Video Memorability Prediction,
MultMed(26), 2024, pp. 4926-4937.
IEEE DOI
2404
Visualization, Semantics, Feature extraction, Predictive models,
Task analysis, Streaming media, Collaboration, Video memorability,
Spatial-temporal features
BibRef
Wang, C.[Chen],
Wang, W.S.[Wen-Shan],
Qiu, Y.H.[Yu-Heng],
Hu, Y.F.[Ya-Fei],
Scherer, S.[Sebastian],
Visual Memorability for Robotic Interestingness via Unsupervised Online
Learning,
ECCV20(II:52-68).
Springer DOI
2011
BibRef
Cohendet, R.,
Demarty, C.,
Duong, N.,
Engilberge, M.,
VideoMem: Constructing, Analyzing, Predicting Short-Term and
Long-Term Video Memorability,
ICCV19(2531-2540)
IEEE DOI
2004
feature extraction, image annotation,
learning (artificial intelligence), neural nets, Time measurement
BibRef
Hu, F.Y.[Fei-Yan],
Smeaton, A.F.[Alan F.],
Image Aesthetics and Content in Selecting Memorable Keyframes from
Lifelogs,
MMMod18(I:608-619).
Springer DOI
1802
BibRef
Basavaraju, S.[Sathisha],
Mittal, P.[Paritosh],
Sur, A.[Arijit],
Image Memorability: The Role of Depth and Motion,
ICIP18(699-703)
IEEE DOI
1809
Optical imaging, Correlation, Predictive models,
Mathematical model, Micromechanical devices, Task analysis,
Image Depth
BibRef
Lahrache, S.,
Ouazzani, R.E.,
Qadi, A.E.,
Visual content learning for visualizations memorability
classification,
ISCV17(1-4)
IEEE DOI
1710
human computer interaction,
classification methods, human brain processes,
image memorability, image processing task,
visual content learning, visual information,
visualization memorability analysis,
BibRef
Shekhar, S.,
Singal, D.,
Singh, H.,
Kedia, M.,
Shetty, A.,
Show and Recall: Learning What Makes Videos Memorable,
CogCV17(2730-2739)
IEEE DOI
1802
Measurement, Predictive models, Semantics, Time factors, Videos, Visualization
BibRef
Lu, J.X.[Jia-Xin],
Xu, M.[Mai],
Wang, Z.L.[Zu-Lin],
Predicting the memorability of natural-scene images,
VCIP16(1-4)
IEEE DOI
1701
Animals
BibRef
Khosla, A.[Aditya],
Bainbridge, W.A.[Wilma A.],
Torralba, A.B.[Antonio B.],
Oliva, A.[Aude],
Modifying the Memorability of Face Photographs,
ICCV13(3200-3207)
IEEE DOI
1403
See also Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope.
BibRef
Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
General References for Matching .