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Uses current views on HVS models of attention.
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1306
Visual attention; Saliency detection; Independent component
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1307
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1309
Topological properties
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1402
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Biological system modeling
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1610
cognition
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SP:IC(39, Part B), No. 1, 2015, pp. 386-404.
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1512
Overt visual attention
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1601
Computational modeling
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MultMedMag(23), No. 1, January 2016, pp. 82-91.
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1603
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Itti, L.,
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1604
image fusion
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Feng, M.,
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WACV16(1-7)
IEEE DOI
1511
Computational modeling
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Gide, M.S.[Milind S.],
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A Locally Weighted Fixation Density-Based Metric for Assessing the
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IP(25), No. 8, August 2016, pp. 3852-3861.
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1608
image processing
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Lahrache, S.,
El Ouazzani, R.,
El Qadi, A.,
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IET-CV(10), No. 6, 2016, pp. 577-584.
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computer vision
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Visual Focus of Attention Estimation With Unsupervised Incremental
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IEEE DOI
1612
BibRef
Earlier:
Unsupervised online learning of visual focus of attention,
AVSS13(25-30)
IEEE DOI
1311
Clustering algorithms
BibRef
Gao, G.Y.[Guang-Yu],
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Ma, K.[Kun],
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Optimal feature combination analysis for crowd saliency prediction,
JVCIR(50), No. 1, 2018, pp. 1-8.
Elsevier DOI
1712
Predicting where people look at in crowd scene.
Crowd, Saliency, Random forest, Visual attention, Face detection
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Wang, W.,
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Deep Visual Attention Prediction,
IP(27), No. 5, May 2018, pp. 2368-2378.
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1804
learning (artificial intelligence), neural nets,
object detection, CNN-based attention models,
saliency detection
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Zheng, Z.,
Zhao, H.,
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Weitlauf, A.S.,
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Design, Development, and Evaluation of a Noninvasive Autonomous
Robot-Mediated Joint Attention Intervention System for Young Children
With ASD,
HMS(48), No. 2, April 2018, pp. 125-135.
IEEE DOI
1804
Cameras, Head, Monitoring, Protocols, Robot kinematics,
Robot sensing systems,
robot-assisted intervention
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Unsupervised Uncertainty Estimation Using Spatiotemporal Cues in
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1804
estimation theory, image colour analysis, image motion analysis,
object detection, spatiotemporal phenomena,
visual attention
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Liu, Q.,
Yang, Y.,
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A robust 3D visual saliency computation model for human fixation
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VCIP17(1-4)
IEEE DOI
1804
feature extraction, image colour analysis, image fusion,
image motion analysis, image resolution, image texture,
Saliency Computational Model
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Assens, M.[Marc],
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SP:IC(69), 2018, pp. 8-14.
Elsevier DOI
1811
BibRef
Earlier:
SaltiNet:
Scan-Path Prediction on 360 Degree Images Using Saliency Volumes,
Egocentric17(2331-2338)
IEEE DOI
1802
Code, Saliency.
WWW Link. Deep learning, Machine learning, Saliency, Scanpath, Visual attention.
Biological system modeling, Computational modeling, Observers,
Predictive models, Training, Visualization
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Cyr, A.[André],
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Bio-inspired visual attention process using spiking neural networks
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DOI Link
1903
BibRef
Fang, Y.,
Zhang, C.,
Huang, H.,
Lei, J.,
Visual Attention Prediction for Stereoscopic Video by Multi-Module
Fully Convolutional Network,
IP(28), No. 11, November 2019, pp. 5253-5265.
IEEE DOI
1909
Visualization, Stereo image processing,
Feature extraction, Computational modeling, Object detection,
fully convolutional network
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Tünnermann, J.[Jan],
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Mertsching, B.[Bärbel],
Saliency From Growing Neural Gas:
Learning Pre-Attentional Structures for a Flexible Attention System,
IP(28), No. 11, November 2019, pp. 5296-5307.
IEEE DOI
1909
Task analysis, Biological system modeling, Modeling,
Image color analysis, Visualization, Object detection, Saliency,
growing neural gas
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Mahdi, A.[Ali],
Qin, J.[Jun],
An extensive evaluation of deep features of convolutional neural
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JVCIR(65), 2019, pp. 102662.
Elsevier DOI
1912
Convolutional neural networks, Feature maps,
Human fixation prediction, Saliency map, Transfer learning
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Min, X.,
Zhai, G.,
Zhou, J.,
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A Multimodal Saliency Model for Videos With High Audio-Visual
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IP(29), 2020, pp. 3805-3819.
IEEE DOI
2002
Audio-visual attention, visual attention, multimodal, saliency,
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Gravitational Laws of Focus of Attention,
PAMI(42), No. 12, December 2020, pp. 2983-2995.
IEEE DOI
2011
Visualization, Computational modeling, Mathematical model,
Task analysis, Brightness, Predictive modeling, Gravity,
gravitational laws
BibRef
Li, K.,
Wu, Z.,
Peng, K.C.,
Ernst, J.,
Fu, Y.,
Guided Attention Inference Network,
PAMI(42), No. 12, December 2020, pp. 2996-3010.
IEEE DOI
2011
BibRef
Earlier:
Tell Me Where to Look: Guided Attention Inference Network,
CVPR18(9215-9223)
IEEE DOI
1812
Neural networks, Semantics, Visualization, Image segmentation,
Supervised learning, Training data,
biased data.
Task analysis, Training
BibRef
Jiang, L.[Lai],
Xu, M.[Mai],
Wang, Z.L.[Zu-Lin],
Sigal, L.[Leonid],
DeepVS2.0: A Saliency-Structured Deep Learning Method for Predicting
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IJCV(129), No. 1, January 2021, pp. 203-224.
Springer DOI
2101
BibRef
Khandelwal, S.,
Sigal, L.,
AttentionRNN: A Structured Spatial Attention Mechanism,
ICCV19(3424-3433)
IEEE DOI
2004
convolutional neural nets,
feedforward neural nets, learning (artificial intelligence),
Computational modeling
BibRef
Yuan, Y.[Yuan],
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Lu, X.Q.[Xiao-Qiang],
Bio-Inspired Representation Learning for Visual Attention Prediction,
Cyber(51), No. 7, July 2021, pp. 3562-3575.
IEEE DOI
2106
Feature extraction, Semantics, Visualization, Object detection,
Cybernetics, Deep learning, Bio-inspired,
visual attention prediction (VAP)
BibRef
Lai, Q.X.[Qiu-Xia],
Khan, S.[Salman],
Nie, Y.W.[Yong-Wei],
Sun, H.[Hanqiu],
Shen, J.B.[Jian-Bing],
Shao, L.[Ling],
Understanding More About Human and Machine Attention in Deep Neural
Networks,
MultMed(23), 2021, pp. 2086-2099.
IEEE DOI
2107
Task analysis, Visualization, Neural networks,
Object segmentation, Image recognition, Reliability, deep learning
BibRef
Shi, X.[Xiang],
Yang, Y.[You],
Liu, Q.[Qiong],
I Understand You:
Blind 3D Human Attention Inference from the Perspective of Third-Person,
IP(30), 2021, pp. 6212-6225.
IEEE DOI
2107
Feature extraction, Estimation, Faces, Solid modeling, Visualization,
Cameras, Human attention inference, scene understanding,
Long-Short-Term-Memory (LSTM)
BibRef
Li, A.[Aoqi],
Chen, Z.Z.[Zhen-Zhong],
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JVCIR(79), 2021, pp. 103206.
Elsevier DOI
2109
Visual attention, Image saliency, Semantic attributes, Object importance
BibRef
Cheng, D.Q.[De-Qiang],
Liu, R.H.[Rui-Hang],
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Zhao, K.[Kai],
Activity guided multi-scales collaboration based on scaled-CNN for
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IVC(114), 2021, pp. 104267.
Elsevier DOI
2109
Saliency prediction, Convolutional neural networks,
Human eye fixations, Deep learning
BibRef
Nan, Z.X.[Zhi-Xiong],
Jiang, J.J.[Jing-Jing],
Gao, X.F.[Xiao-Feng],
Zhou, S.P.[San-Ping],
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Wei, P.[Ping],
Zheng, N.N.[Nan-Ning],
Predicting Task-Driven Attention via Integrating Bottom-Up Stimulus
and Top-Down Guidance,
IP(30), 2021, pp. 8293-8305.
IEEE DOI
2110
Task analysis, Predictive models, Feature extraction,
Image color analysis, Visualization, Computer architecture,
task-driven
BibRef
Xia, C.[Chen],
Han, J.W.[Jun-Wei],
Zhang, D.W.[Ding-Wen],
Evaluation of Saccadic Scanpath Prediction: Subjective Assessment
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PAMI(43), No. 12, December 2021, pp. 4378-4395.
IEEE DOI
2112
Measurement, Predictive models, Visualization, Feature extraction,
Computational modeling, Visual databases, Visual attention,
semantic hashing
BibRef
Beelders, T.[Tanya],
Dollman, G.[Gavin],
Virtual Prospecting in Paleontology Using a Drone-Based Orthomosaic Map:
An Eye Movement Analysis,
IJGI(10), No. 11, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Zhang, H.[Hao],
Peng, G.Q.[Guo-Qin],
Wu, Z.C.[Zhi-Chao],
Gong, J.[Jian],
Xu, D.[Dan],
Shi, H.Z.[Hong-Zhen],
MAM: A multipath attention mechanism for image recognition,
IET-IPR(16), No. 3, 2022, pp. 691-702.
DOI Link
2202
BibRef
Long, X.[Xiang],
de Melo, G.[Gerard],
He, D.L.[Dong-Liang],
Li, F.[Fu],
Chi, Z.Z.[Zhi-Zhen],
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Gan, C.[Chuang],
Purely Attention Based Local Feature Integration for Video
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PAMI(44), No. 4, April 2022, pp. 2140-2154.
IEEE DOI
2203
Feature extraction, Convolution, Computational modeling, Plugs,
Task analysis, Video classification, action recognition,
computer vision
BibRef
Long, X.,
Gan, C.,
de Melo, G.,
Wu, J.,
Liu, X.,
Wen, S.,
Attention Clusters: Purely Attention Based Local Feature Integration
for Video Classification,
CVPR18(7834-7843)
IEEE DOI
1812
Feature extraction, Task analysis, Recurrent neural networks,
Computational modeling, Optical imaging, Optical network units
BibRef
Ding, G.Q.[Guan-Qun],
Imamoglu, N.[Nevrez],
Caglayan, A.[Ali],
Murakawa, M.[Masahiro],
Nakamura, R.[Ryosuke],
SalFBNet: Learning pseudo-saliency distribution via feedback
convolutional networks,
IVC(120), 2022, pp. 104395.
Elsevier DOI
2204
Better learn distinguishable eye-fixation-based features.
Feedback networks, Human gaze, Pseudo-saliency,
Selective fixation and non-fixation error
BibRef
Lateef, F.[Fahad],
Kas, M.[Mohamed],
Ruichek, Y.[Yassine],
Saliency Heat-Map as Visual Attention for Autonomous Driving Using
Generative Adversarial Network (GAN),
ITS(23), No. 6, June 2022, pp. 5360-5373.
IEEE DOI
2206
Visualization, Vehicles, Generative adversarial networks,
Computational modeling, Autonomous vehicles, Predictive models,
scene understanding
BibRef
Zhu, Y.C.[Yu-Cheng],
Zhai, G.T.[Guang-Tao],
Yang, Y.[Yiwei],
Duan, H.Y.[Hui-Yu],
Min, X.K.[Xiong-Kuo],
Yang, X.K.[Xiao-Kang],
Viewing Behavior Supported Visual Saliency Predictor for 360 Degree
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CirSysVideo(32), No. 7, July 2022, pp. 4188-4201.
IEEE DOI
2207
Visualization, Videos, Feature extraction, Head, Predictive models,
Solid modeling, Magnetic heads, Virtual reality, visual attention,
head and eye movement
BibRef
Li, T.[Tao],
Ma, J.W.[Jin-Wen],
Attention Mechanism Based Mixture of Gaussian Processes,
PRL(161), 2022, pp. 130-136.
Elsevier DOI
2209
Gaussian processes, Attention, Mixture model
BibRef
Gomez, T.[Tristan],
Ling, S.[Suiyi],
Fréour, T.[Thomas],
Mouchère, H.[Harold],
BR-NPA: A non-parametric high-resolution attention model to improve
the interpretability of attention,
PR(132), 2022, pp. 108927.
Elsevier DOI
2209
Deep learning, Interpretability, Spatial attention, Resolution, Non-parametric
BibRef
Veiga, T.[Tiago],
Renoux, J.[Jennifer],
From Reactive to Active Sensing:
A Survey on Information Gathering in Decision-Theoretic Planning,
Surveys(55), No. 13s, July 2023, pp. xx-yy.
DOI Link
2309
information gathering, Decision-theoretic planning, active sensing
BibRef
Ma, Y.W.[Yi-Wei],
Ji, J.Y.[Jia-Yi],
Sun, X.S.[Xiao-Shuai],
Zhou, Y.[Yiyi],
Wu, Y.J.[Yong-Jian],
Huang, F.Y.[Fei-Yue],
Ji, R.R.[Rong-Rong],
Knowing What it is: Semantic-Enhanced Dual Attention Transformer,
MultMed(25), 2023, pp. 3723-3736.
IEEE DOI Code:
WWW Link.
2310
BibRef
Lu, E.H.C.[Eric Hsueh-Chan],
Lin, Y.R.[You-Ru],
A Self-Attention Model for Next Location Prediction Based on Semantic
Mining,
IJGI(12), No. 10, 2023, pp. 420.
DOI Link
2311
BibRef
Wang, S.[Shuo],
Wu, Z.H.[Zhi-Hao],
Hu, X.B.[Xiao-Bo],
Lin, Y.F.[You-Fang],
Lv, K.[Kai],
Skill-Based Hierarchical Reinforcement Learning for Target Visual
Navigation,
MultMed(25), 2023, pp. 8920-8932.
IEEE DOI
2312
find a target object.
BibRef
Ge, C.J.[Chong-Jian],
Song, Y.B.[Yi-Bing],
Ma, C.[Chao],
Qi, Y.[Yuankai],
Luo, P.[Ping],
Rethinking Attentive Object Detection via Neural Attention Learning,
IP(33), 2024, pp. 1726-1739.
IEEE DOI
2403
Object detection, Proposals, Detectors, Training, Visualization,
Convolutional neural networks, Head, Object detection,
neural attention learning
BibRef
Han, G.[Gaoge],
Huang, S.L.[Shao-Li],
Zhao, F.[Fang],
Tang, J.L.[Jing-Lei],
SIAM: A parameter-free, Spatial Intersection Attention Module,
PR(153), 2024, pp. 110509.
Elsevier DOI
2405
3-D attention module, Parameter-free, Convolutional neural networks
BibRef
Shi, B.F.[Bai-Feng],
Darrell, T.J.[Trevor J.],
Wang, X.[Xin],
Top-Down Visual Attention from Analysis by Synthesis,
CVPR23(2102-2112)
IEEE DOI
2309
BibRef
Mondal, S.[Sounak],
Yang, Z.B.[Zhi-Bo],
Ahn, S.[Seoyoung],
Samaras, D.[Dimitris],
Zelinsky, G.[Gregory],
Hoai, M.[Minh],
Gazeformer: Scalable, Effective and Fast Prediction of Goal-Directed
Human Attention,
CVPR23(1441-1450)
IEEE DOI
2309
BibRef
Paula, B.[Beatriz],
Moreno, P.[Plinio],
Learning to Search for and Detect Objects in Foveal Images Using Deep
Learning,
IbPRIA23(223-237).
Springer DOI
2307
Evaluate fixation points.
BibRef
Zhong, S.S.[Shan-Shan],
Wen, W.[Wushao],
Qin, J.H.[Jing-Hui],
SPEM: Self-adaptive Pooling Enhanced Attention Module for Image
Recognition,
MMMod23(II: 41-53).
Springer DOI
2304
BibRef
Kadner, F.[Florian],
Thomas, T.[Tobias],
Hoppe, D.[David],
Rothkopf, C.A.[Constantin A.],
Improving saliency models' predictions of the next fixation with
humans' intrinsic cost of gaze shifts,
WACV23(2103-2113)
IEEE DOI
2302
Costs, Heuristic algorithms, Computational modeling,
Decision making, Predictive models, Benchmark testing,
Applications: Psychology and cognitive science
BibRef
Wang, H.Y.[Han-Yu],
Gupta, K.[Kamal],
Davis, L.S.[Larry S.],
Shrivastava, A.[Abhinav],
Neural Space-Filling Curves,
ECCV22(VII:418-434).
Springer DOI
2211
WWW Link. To get a good scan order.
BibRef
Zhang, K.[Kepei],
Lu, M.Q.[Mei-Qi],
Lu, Z.[Zheng],
Zhang, X.T.[Xue-Tao],
Scanpath Prediction Via Semantic Representation of the Scene,
ICIP22(1976-1980)
IEEE DOI
2211
Object instances and backgrounds in scenes, and uses the attention
mechanism to learn the semantic correlation between objects.
Visualization, Image segmentation, Graphical models, Correlation,
Semantics, Reinforcement learning, Predictive models,
Inverse Reinforcement Learning
BibRef
Xu, Y.X.[Yu-Xiao],
Huo, Y.K.[Yong-Kai],
Song, Y.[Yukai],
Panoramic Viewport Prediction Relying on Emotional Attention Map,
ICIP22(1751-1755)
IEEE DOI
2211
Visualization, Estimation, Immersive experience, Predictive models,
Benchmark testing, Trajectory, Panoramic video,
Emotional attention
BibRef
Petryk, S.[Suzanne],
Dunlap, L.[Lisa],
Nasseri, K.[Keyan],
Gonzalez, J.[Joseph],
Darrell, T.J.[Trevor J.],
Rohrbach, A.[Anna],
On Guiding Visual Attention with Language Specification,
CVPR22(18071-18081)
IEEE DOI
2210
Visualization, Image recognition, Training data,
Feature extraction, Pattern recognition, Numerical models, Visual reasoning
BibRef
Chen, Q.[Qiang],
Wu, Q.[Qiman],
Wang, J.[Jian],
Hu, Q.H.[Qing-Hao],
Hu, T.[Tao],
Ding, E.[Errui],
Cheng, J.[Jian],
Wang, J.D.[Jing-Dong],
MixFormer: Mixing Features across Windows and Dimensions,
CVPR22(5239-5249)
IEEE DOI
2210
Code, Attention.
WWW Link. Couplings, Codes, Convolution, Bidirectional control, Transformers,
Pattern recognition, Recognition: detection, categorization, retrieval
BibRef
Long, F.C.[Fu-Chen],
Qiu, Z.F.[Zhao-Fan],
Pan, Y.W.[Ying-Wei],
Yao, T.[Ting],
Luo, J.B.[Jie-Bo],
Mei, T.[Tao],
Stand-Alone Inter-Frame Attention in Video Models,
CVPR22(3182-3191)
IEEE DOI
2210
Code, Attention.
WWW Link. Convolutional codes, Weight measurement, Deep learning,
Solid modeling, Computational modeling, Transformers,
Video analysis and understanding
BibRef
Arar, M.[Moab],
Shamir, A.[Ariel],
Bermano, A.H.[Amit H.],
Learned Queries for Efficient Local Attention,
CVPR22(10831-10842)
IEEE DOI
2210
Convolutional codes, Image synthesis, Memory management,
Transformers, Complexity theory, Pattern recognition, retrieval,
Recognition: detection
BibRef
Yang, Z.B.[Zhi-Bo],
Mondal, S.[Sounak],
Ahn, S.[Seoyoung],
Zelinsky, G.[Gregory],
Hoai, M.[Minh],
Samaras, D.[Dimitris],
Target-Absent Human Attention,
ECCV22(IV:52-68).
Springer DOI
2211
BibRef
Chen, Y.P.[Yu-Pei],
Yang, Z.B.[Zhi-Bo],
Chakraborty, S.[Souradeep],
Mondal, S.[Sounak],
Ahn, S.[Seoyoung],
Samaras, D.[Dimitris],
Hoai, M.[Minh],
Zelinsky, G.[Gregory],
Characterizing Target-absent Human Attention,
Gaze22(5027-5036)
IEEE DOI
2210
Conferences, Object detection, Machine learning, Detectors,
Predictive models, Behavioral sciences
BibRef
Jha, A.[Abhishek],
Seifi, S.[Soroush],
Tuytelaars, T.[Tinne],
SimGlim: Simplifying glimpse based active visual reconstruction,
WACV23(269-278)
IEEE DOI
2302
BibRef
Earlier: A2, A1, A3:
Glimpse-Attend-and-Explore: Self-Attention for Active Visual
Exploration,
ICCV21(16117-16126)
IEEE DOI
2203
Visualization, Reconstruction algorithms, Predictive models,
Transformers, Data models, Task analysis,
image and video synthesis.
Representation learning, Adaptation models,
Uncertainty, Reinforcement learning, grouping and shape
BibRef
Leyva, R.[Roberto],
Sanchez, V.[Victor],
Video Memorability Prediction Via Late Fusion of Deep Multi-Modal
Features,
ICIP21(2488-2492)
IEEE DOI
2201
Visualization, Fuses, Social networking (online),
Computational modeling, Neural networks, Feature extraction, fusion
BibRef
Chen, Q.P.[Qi-Pin],
Shi, Z.Y.[Zhen-Yu],
Zuo, Z.[Zhen],
Fu, J.M.[Jin-Miao],
Sun, Y.[Yi],
Two-Stream Hybrid Attention Network for Multimodal Classification,
ICIP21(359-363)
IEEE DOI
2201
Image processing, multimodal classification, hybrid attention mechanism
BibRef
Martins, P.H.[Pedro Henrique],
Niculae, V.[Vlad],
Marinho, Z.[Zita],
Martins, A.F.T.[André F. T.],
Sparse and Structured Visual Attention,
ICIP21(379-383)
IEEE DOI
2201
Visualization, Image processing, Knowledge discovery,
Task analysis, Attention, Structured Sparsity, Total Variation
BibRef
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Martins, A.F.T.[André F. T.],
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VIPriors21(1047-1056)
IEEE DOI
2112
Jacobian matrices, Visualization, Shape,
Computational modeling, Neural networks, MIMICs
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Visual Focus of Attention Estimation in 3D Scene with an Arbitrary
Number of Targets,
Gaze21(3147-3155)
IEEE DOI
2109
Deep learning, Training, Visualization,
TV, Estimation, Usability
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Zhang, M.Y.[Ming-Yuan],
Zhao, H.Y.[Hai-Yu],
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Efficient Attention: Attention with Linear Complexities,
WACV21(3530-3538)
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2106
Computational modeling,
Memory management, Estimation, Object detection, Detectors
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Dai, Y.M.[Yi-Mian],
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Attention as Activation,
ICPR21(9156-9163)
IEEE DOI
2105
Aggregates, Performance gain
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Krishna, O.[Onkar],
Irie, G.[Go],
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Kashino, K.[Kunio],
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Translating Adult's Focus of Attention to Elderly's,
ICPR21(563-568)
IEEE DOI
2105
Training, Legged locomotion, Computational modeling,
Senior citizens, Estimation, Predictive models, Observers
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Efremova, N.,
Hajimirza, N.,
Bassett, D.,
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Understanding consumer attention on mobile devices,
FG20(919-919)
IEEE DOI
2102
Mobile handsets, Social networking (online), Generators,
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Ajmal, A.[Aisha],
Al-Sahaf, H.[Harith],
Hollitt, C.[Christopher],
Salient Motion Features for Visual Attention Models,
IVCNZ20(1-6)
IEEE DOI
2012
Visualization, Image color analysis, Computational modeling,
Estimation, Color, Feature extraction, Optical flow, HSV
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Look Here! A Parametric Learning Based Approach to Redirect Visual
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ECCV20(XXIII:343-361).
Springer DOI
2011
BibRef
Uzkent, B.,
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Learning When and Where to Zoom With Deep Reinforcement Learning,
CVPR20(12342-12351)
IEEE DOI
2008
Task analysis, Spatial resolution, Training, Random variables,
Satellites
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Yang, Z.,
Huang, L.,
Chen, Y.,
Wei, Z.,
Ahn, S.,
Zelinsky, G.,
Samaras, D.,
Hoai, M.,
Predicting Goal-Directed Human Attention Using Inverse Reinforcement
Learning,
CVPR20(190-199)
IEEE DOI
2008
Visualization, Task analysis, Predictive models, Search problems,
Learning (artificial intelligence), Computational modeling, Context modeling
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Wang, L.Z.[Le-Zi],
Wu, Z.Y.[Zi-Yan],
Karanam, S.[Srikrishna],
Peng, K.C.[Kuan-Chuan],
Singh, R.V.[Rajat Vikram],
Liu, B.[Bo],
Metaxas, D.N.[Dimitris N.],
Sharpen Focus: Learning With Attention Separability and Consistency,
ICCV19(512-521)
IEEE DOI
2004
feature extraction, image classification, image representation,
learning (artificial intelligence), neural nets, Benchmark testing
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Abolghasemi, P.[Pooya],
Mazaheri, A.[Amir],
Shah, M.[Mubarak],
Boloni, L.[Ladislau],
Pay Attention! - Robustifying a Deep Visuomotor Policy Through
Task-Focused Visual Attention,
CVPR19(4249-4257).
IEEE DOI
2002
BibRef
Liu, X.H.[Xi-Hui],
Wang, Z.H.[Zi-Hao],
Shao, J.[Jing],
Wang, X.G.[Xiao-Gang],
Li, H.S.[Hong-Sheng],
Improving Referring Expression Grounding With Cross-Modal
Attention-Guided Erasing,
CVPR19(1950-1959).
IEEE DOI
2002
BibRef
Guo, H.[Hao],
Zheng, K.[Kang],
Fan, X.C.[Xiao-Chuan],
Yu, H.K.[Hong-Kai],
Wang, S.[Song],
Visual Attention Consistency Under Image Transforms for Multi-Label
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CVPR19(729-739).
IEEE DOI
2002
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Cuculo, V.[Vittorio],
d'Amelio, A.[Alessandro],
Grossi, G.[Giuliano],
Lanzarotti, R.[Raffaella],
Worldly Eyes on Video: Learnt vs. Reactive Deployment of Attention to
Dynamic Stimuli,
CIAP19(I:128-138).
Springer DOI
1909
BibRef
Leonardi, M.[Marco],
Celona, L.[Luigi],
Napoletano, P.[Paolo],
Bianco, S.[Simone],
Schettini, R.[Raimondo],
Manessi, F.[Franco],
Rozza, A.[Alessandro],
Image Memorability Using Diverse Visual Features and Soft Attention,
CIAP19(II:171-180).
Springer DOI
1909
BibRef
Fajtl, J.,
Argyriou, V.,
Monekosso, D.,
Remagnino, P.,
AMNet: Memorability Estimation with Attention,
CVPR18(6363-6372)
IEEE DOI
1812
Visualization, Feature extraction, Estimation, Task analysis,
Neural networks, Training
BibRef
Wloka, C.,
Kotseruba, I.,
Tsotsos, J.K.,
Active Fixation Control to Predict Saccade Sequences,
CVPR18(3184-3193)
IEEE DOI
1812
Visualization, Computational modeling, Retina, Predictive models,
Streaming media
BibRef
Adeli, H.,
Zelinsky, G.,
Deep-BCN: Deep Networks Meet Biased Competition to Create a
Brain-Inspired Model of Attention Control,
Cognitive18(2013-201310)
IEEE DOI
1812
Visualization, Brain modeling, Computational modeling,
Object detection, Search problems
BibRef
Fan, H.Q.[Hao-Qi],
Zhou, J.T.[Jia-Tong],
Stacked Latent Attention for Multimodal Reasoning,
CVPR18(1072-1080)
IEEE DOI
1812
Cognition, Task analysis, Computational modeling, Visualization,
Computer architecture, Stacking, Knowledge discovery
BibRef
Wei, P.,
Liu, Y.,
Shu, T.,
Zheng, N.,
Zhu, S.,
Where and Why are They Looking? Jointly Inferring Human Attention and
Intentions in Complex Tasks,
CVPR18(6801-6809)
IEEE DOI
1812
Task analysis, Videos, Feature extraction, Skeleton, Bridges
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Palenichka, R.[Roman],
Falcon, R.[Rafael],
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A Computational Model of Multi-scale Spatiotemporal Attention in Video
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ICIAR18(125-135).
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1807
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Li, A.,
Chen, Z.,
Individual trait oriented scanpath prediction for visual attention
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ICIP17(3745-3749)
IEEE DOI
1803
Computational modeling, Kernel, Mathematical model, Observers,
Predictive models, Semantics, Visualization, individuality,
visual attention
BibRef
Weibel, J.B.,
Tan, H.L.,
Lu, S.,
An integrated approach to visual attention modelling using
spatial-temporal saliency and objectness,
ICIP17(440-444)
IEEE DOI
1803
Computational modeling, Histograms, Integrated optics,
Optical imaging, Sun, Visualization
BibRef
Kümmerer, M.,
Wallis, T.S.A.,
Gatys, L.A.,
Bethge, M.,
Understanding Low- and High-Level Contributions to Fixation
Prediction,
ICCV17(4799-4808)
IEEE DOI
1802
feature extraction, image classification,
neural nets, object detection, object recognition,
Predictive models
BibRef
Li, Z.,
Yang, Y.,
Liu, X.,
Zhou, F.,
Wen, S.,
Xu, W.,
Dynamic Computational Time for Visual Attention,
CEFR-LCV17(1199-1209)
IEEE DOI
1802
Adaptation models, Computational modeling, Image recognition,
Neural networks, Random access memory, Training, Visualization
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Gorji, S.[Siavash],
Clark, J.J.[James J.],
Going from Image to Video Saliency: Augmenting Image Salience with
Dynamic Attentional Push,
CVPR18(7501-7511)
IEEE DOI
1812
BibRef
Earlier:
Attentional Push: A Deep Convolutional Network for Augmenting Image
Salience with Shared Attention Modeling in Social Scenes,
CVPR17(3472-3481)
IEEE DOI
1711
Visualization, Computational modeling, Spatiotemporal phenomena,
Color, Dynamics, Fuses, Optical imaging.
Feature extraction, Head, Neural networks,
Predictive models, Training
BibRef
Kahou, S.E.[Samira Ebrahimi],
Michalski, V.[Vincent],
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RATM: Recurrent Attentive Tracking Model,
MotionRep17(1613-1622)
IEEE DOI
1709
Computational modeling, Feature extraction, Proposals,
Recurrent neural networks, Standards, Training
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Wang, J.,
Tavakoli, H.R.[Hamed R.],
Laaksonen, J.[Jorma],
Fixation Prediction in Videos Using Unsupervised Hierarchical
Features,
DeepLearn-T17(2225-2232)
IEEE DOI
1709
BibRef
Earlier: A2, A3, Only:
Bottom-Up Fixation Prediction Using Unsupervised Hierarchical Models,
Assist16(I: 287-302).
Springer DOI
1704
Computational modeling, Estimation, Feature extraction,
Predictive models, Training, Videos, Visualization
BibRef
Chen, J.Z.[Jia-Zhong],
Li, Y.Z.[Yi-Zhang],
Fan, Y.B.[Ye-Bin],
Wu, W.M.[Wei-Min],
Wang, X.[Xian],
Cao, H.[Hua],
Chen, Y.[Yang],
Investigation of mobile surroundings for visual attention based on
image perception model,
VCIP16(1-4)
IEEE DOI
1701
Estimation
BibRef
Rahman, I.M.H.,
Hollitt, C.,
Zhang, M.,
A dynamic feature map integration approach for predicting human
fixation,
ICVNZ16(1-6)
IEEE DOI
1701
Computational modeling
BibRef
Wei, Q.,
Zhai, G.,
Hu, C.,
Min, X.,
Visual attention analysis and prediction on human faces with mole,
VCIP16(1-4)
IEEE DOI
1701
Computational modeling
BibRef
Thomas, C.[Christopher],
Kovashka, A.[Adriana],
Chiarulli, D.[Donald],
Levitan, S.[Steven],
A Visual Attention Algorithm Designed for Coupled Oscillator
Acceleration,
ECVW16(828-836)
IEEE DOI
1612
BibRef
Shih, K.J.[Kevin J.],
Singh, S.[Saurabh],
Hoiem, D.[Derek],
Where to Look: Focus Regions for Visual Question Answering,
CVPR16(4613-4621)
IEEE DOI
1612
BibRef
Rai, Y.,
Le Callet, P.,
Cheung, G.,
Quantifying the relation between perceived interest and visual
salience during free viewing using trellis based optimization,
IVMSP16(1-5)
IEEE DOI
1608
Hidden Markov models
BibRef
Li, Y.,
Guo, X.,
Wang, H.,
Spatio-temporal quality pooling adaptive to distortion distribution
and visual attention,
VCIP15(1-4)
IEEE DOI
1605
Adaptation models
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Khosla, A.[Aditya],
Raju, A.S.[Akhil S.],
Torralba, A.B.[Antonio B.],
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Understanding and Predicting Image Memorability at a Large Scale,
ICCV15(2390-2398)
IEEE DOI
1602
Dataset, Memorability.
WWW Link. Benchmark testing
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Dubey, R.,
Peterson, J.,
Khosla, A.,
Yang, M.H.,
Ghanem, B.,
What Makes an Object Memorable?,
ICCV15(1089-1097)
IEEE DOI
1602
Computer vision
BibRef
Cao, C.S.[Chun-Shui],
Liu, X.M.[Xian-Ming],
Yang, Y.[Yi],
Yu, Y.N.[Yi-Nan],
Wang, J.[Jiang],
Wang, Z.L.[Zi-Lei],
Huang, Y.Z.[Yong-Zhen],
Wang, L.[Liang],
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Xu, W.[Wei],
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Look and Think Twice: Capturing Top-Down Visual Attention with
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ICCV15(2956-2964)
IEEE DOI
1602
Biological neural networks
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Informed Perspectives on Human Annotation Using Neural Signals,
MMMod16(II: 315-327).
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1601
Understanding how p[eople do it.
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Elafoudi, G.[Georgia],
Stankovic, V.[Vladimir],
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Springer DOI
1511
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Amengual, X.[Xesca],
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1511
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Boukhechba, M.[Mehdi],
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1511
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Sattar, H.[Hosnieh],
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CVPR15(981-990)
IEEE DOI
1510
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Zhao, J.P.[Jia-Ping],
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Fixation bank: Learning to reweight fixation candidates,
CVPR15(3174-3182)
IEEE DOI
1510
BibRef
Ma, B.,
Zhou, J.,
Gu, X.,
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Zhang, Y.,
Guo, X.,
A new approach to create 3D fixation density maps for stereoscopic
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3DTV-CON15(1-4)
IEEE DOI
1508
Accuracy
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Ultra high definition video saliency database,
VCIP14(97-100)
IEEE DOI
1504
video databases
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1504
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IPTA14(1-1)
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1503
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ICPR14(483-488)
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ICPR14(2691-2696)
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Karayev, S.[Sergey],
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ICIP13(211-215)
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1402
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Nakashima, Y.[Yuta],
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ICIP13(191-195)
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1402
Cameras
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Multi-scale visual attention & saliency modelling with decision
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ICIP13(216-220)
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Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Human Attention, Gaze, Eye Tracking .