13.6.12 Image and Video Memorability

Chapter Contents (Back)
Memorable Image. Memorable Video.
See also Aesthetic Quality, Aesthetic Evaluation.
See also Visual Sentiment Evaluation.

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


Dumont, T.[Théo], Hevia, J.S.[Juan Segundo], Fosco, C.L.[Camilo L.],
Modular Memorability: Tiered Representations for Video Memorability Prediction,
CVPR23(10751-10760)
IEEE DOI 2309
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 .


Last update:May 6, 2024 at 15:50:14