On the public citation graph
End-to-End Saliency Mapping via Probability Distribution Prediction
0 signed · 176 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-10602-1_48openalex-snapshot
Microsoft COCO: Common Objects in Context
inferredcites →https://doi.org/10.1007/978-3-642-33709-3_8openalex-snapshot
Depth Matters: Influence of Depth Cues on Visual Saliency
inferredcites →https://doi.org/10.1007/978-3-642-33709-3_9openalex-snapshot
Quaternion-Based Spectral Saliency Detection for Eye Fixation Prediction
inferredcites →https://doi.org/10.1007/978-94-009-3833-5_5openalex-snapshot
Shifts in Selective Visual Attention: Towards the Underlying Neural Circuitry
inferredcites →https://doi.org/10.1016/0010-0285(80)90005-5openalex-snapshot
A feature-integration theory of attention
inferredcites →https://doi.org/10.1016/s0042-6989(99)00163-7openalex-snapshot
A saliency-based search mechanism for overt and covert shifts of visual attention
inferredcites →https://doi.org/10.1016/s0166-4115(96)x8067-1openalex-snapshot
Visual Attention and Cognition
inferredcites →https://doi.org/10.1109/34.730558openalex-snapshot
A model of saliency-based visual attention for rapid scene analysis
inferredcites →https://doi.org/10.1109/cvpr.2007.383267openalex-snapshot
Saliency Detection: A Spectral Residual Approach
inferredcites →https://doi.org/10.1109/cvpr.2011.5995506openalex-snapshot
Saliency estimation using a non-parametric low-level vision model
inferredcites →https://doi.org/10.1109/cvpr.2012.6248093openalex-snapshot
Discriminative spatial saliency for image classification
inferredcites →https://doi.org/10.1109/cvpr.2014.358openalex-snapshot
Large-Scale Optimization of Hierarchical Features for Saliency Prediction in Natural Images
inferredcites →https://doi.org/10.1109/cvpr.2015.7298710openalex-snapshot
SALICON: Saliency in Context
inferredcites →https://doi.org/10.1109/cvpr.2015.7298965openalex-snapshot
Fully convolutional networks for semantic segmentation
inferredcites →https://doi.org/10.1109/cvpr.2015.7299141openalex-snapshot
Label Consistent Quadratic Surrogate model for visual saliency prediction
inferredcites →https://doi.org/10.1109/icassp.2000.862057openalex-snapshot
A new distance measure for probability distribution function of mixture type
inferredcites →https://doi.org/10.1109/iccv.2009.5459240openalex-snapshot
Image saliency by isocentric curvedness and color
inferredcites →https://doi.org/10.1109/iccv.2009.5459462openalex-snapshot
Learning to predict where humans look
inferredcites →https://doi.org/10.1109/iccv.2009.5459467openalex-snapshot
A framework for visual saliency detection with applications to image thumbnailing
inferredcites →https://doi.org/10.1109/iccv.2013.26openalex-snapshot
Saliency Detection: A Boolean Map Approach
inferredcites →https://doi.org/10.1109/iccv.2015.38openalex-snapshot
SALICON: Reducing the Semantic Gap in Saliency Prediction by Adapting Deep Neural Networks
inferredcites →https://doi.org/10.1109/icip.2009.5413815openalex-snapshot
Saliency detection for content-aware image resizing
inferredcites →https://doi.org/10.1109/icme.2015.7177450openalex-snapshot
PET: An eye-tracking dataset for animal-centric Pascal object classes
inferredcites →https://doi.org/10.1109/tip.2017.2710620openalex-snapshot
DeepFix: A Fully Convolutional Neural Network for Predicting Human Eye Fixations
inferredcites →https://doi.org/10.1109/tnnls.2015.2480683openalex-snapshot
Reconciling Saliency and Object Center-Bias Hypotheses in Explaining Free-Viewing Fixations
inferredcites →https://doi.org/10.1109/tpami.2011.146openalex-snapshot
Image Signature: Highlighting Sparse Salient Regions
inferredcites →https://doi.org/10.1109/tpami.2012.89openalex-snapshot
State-of-the-Art in Visual Attention Modeling
inferredcites →https://doi.org/10.1109/tpami.2013.108openalex-snapshot
Low-Level Spatiochromatic Grouping for Saliency Estimation
inferredcites →https://doi.org/10.1109/tpami.2016.2577031openalex-snapshot
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1167/11.3.9openalex-snapshot
Learning a saliency map using fixated locations in natural scenes
inferredcites →https://doi.org/10.1167/8.7.32openalex-snapshot
SUN: A Bayesian framework for saliency using natural statistics
inferredcites →https://doi.org/10.1364/ol.38.000700openalex-snapshot
Saliency detection using regional histograms
inferredcites →https://doi.org/10.2390/biecoll-icvs2007-148openalex-snapshot
Attention Based Auto Image Cropping
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1411.1045openalex-snapshot
Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet
inferredcites →https://doi.org/10.48550/arxiv.1504.06755openalex-snapshot
TurkerGaze: Crowdsourcing Saliency with Webcam based Eye Tracking
inferredcites →https://doi.org/10.48550/arxiv.1507.01422openalex-snapshot
End-to-end Convolutional Network for Saliency Prediction
inferredcites →https://doi.org/10.7551/mitpress/7503.003.0073openalex-snapshot
Graph-Based Visual Saliency
inferredcites →https://doi.org/10.7551/mitpress/7503.003.0091openalex-snapshot
A Nonparametric Approach to Bottom-Up Visual Saliency
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-01270-0_47openalex-snapshot
Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics
inferred← citeshttps://doi.org/10.1007/978-3-030-11021-5_25openalex-snapshot
PathGAN: Visual Scanpath Prediction with Generative Adversarial Networks
inferred← citeshttps://doi.org/10.1007/978-3-030-20085-5_9openalex-snapshot
Advanced Statistical Methods for Eye Movement Analysis and Modelling: A Gentle Introduction
inferred← citeshttps://doi.org/10.1007/978-3-030-39343-4_15openalex-snapshot
Towards Capturing Sonographic Experience: Cognition-Inspired Ultrasound Video Saliency Prediction
inferred← citeshttps://doi.org/10.1007/978-3-030-58558-7_25openalex-snapshot
Unified Image and Video Saliency Modeling
inferred← citeshttps://doi.org/10.1007/978-3-319-70169-1_29openalex-snapshot
Attentive Models in Vision: Computing Saliency Maps in the Deep Learning Era
inferred← citeshttps://doi.org/10.1007/978-981-19-2290-9_5openalex-snapshot
Vision-Based Human Attention Modelling
inferred← citeshttps://doi.org/10.1007/978-981-32-9291-8_6openalex-snapshot
DeepAttent: Saliency Prediction with Deep Multi-scale Residual Network
inferred← citeshttps://doi.org/10.1007/978-981-99-5994-5_27openalex-snapshot
Human Eye Fixations Prediction for Visual Attention Using CNN - A Survey
inferred← citeshttps://doi.org/10.1007/s00521-025-11812-3openalex-snapshot
Modeling human attention: analyzing scanpaths and visual features in fixation prediction with transformer-based deep learning
inferred← citeshttps://doi.org/10.1007/s00530-021-00796-4openalex-snapshot
Visual saliency prediction using multi-scale attention gated network
inferred← citeshttps://doi.org/10.1007/s10489-022-03647-5openalex-snapshot
FGO-Net: Feature and Gaussian Optimization Network for visual saliency prediction
inferred← citeshttps://doi.org/10.1007/s11042-018-6770-2openalex-snapshot
Learning adaptive contrast combinations for visual saliency detection
inferred← citeshttps://doi.org/10.1007/s12539-022-00510-6openalex-snapshot
Identifying Visual Attention Features Accurately Discerning Between Autism and Typically Developing: a Deep Learning Framework
inferred← citeshttps://doi.org/10.1016/j.cviu.2018.03.005openalex-snapshot
Top-down saliency detection driven by visual classification
inferred← citeshttps://doi.org/10.1016/j.dsp.2021.103289openalex-snapshot
Attentive and context-aware deep network for saliency prediction on omni-directional images
inferred← citeshttps://doi.org/10.1016/j.engappai.2021.104204openalex-snapshot
A better way of extracting dominant colors using salient objects with semantic segmentation
inferred← citeshttps://doi.org/10.1016/j.image.2016.11.003openalex-snapshot
A comparative study for feature integration strategies in dynamic saliency estimation
inferred← citeshttps://doi.org/10.1016/j.image.2019.05.001openalex-snapshot
A behaviorally inspired fusion approach for computational audiovisual saliency modeling
inferred← citeshttps://doi.org/10.1016/j.image.2019.115694openalex-snapshot
Hedging static saliency models to predict dynamic saliency
inferred← citeshttps://doi.org/10.1016/j.image.2022.116671openalex-snapshot
A compact deep architecture for real-time saliency prediction
inferred← citeshttps://doi.org/10.1016/j.imavis.2020.103887openalex-snapshot
EML-NET: An Expandable Multi-Layer NETwork for saliency prediction
inferred← citeshttps://doi.org/10.1016/j.imavis.2021.104149openalex-snapshot
SalED: Saliency prediction with a pithy encoder-decoder architecture sensing local and global information
inferred← citeshttps://doi.org/10.1016/j.imavis.2021.104267openalex-snapshot
Activity guided multi-scales collaboration based on scaled-CNN for saliency prediction
inferred← citeshttps://doi.org/10.1016/j.ins.2023.119625openalex-snapshot
Perceptual loss guided Generative adversarial network for saliency detection
inferred← citeshttps://doi.org/10.1016/j.jvcir.2019.102611openalex-snapshot
A multiscale dilated dense convolutional network for saliency prediction with instance-level attention competition
inferred← citeshttps://doi.org/10.1016/j.jvcir.2019.102662openalex-snapshot
An extensive evaluation of deep featuresof convolutional neural networks for saliency prediction of human visual attention
inferred← citeshttps://doi.org/10.1016/j.jvcir.2020.102931openalex-snapshot
Exploiting object features in deep gaze prediction models
inferred← citeshttps://doi.org/10.1016/j.jvcir.2021.103031openalex-snapshot
Saliency detection via cross-scale deep inference
inferred← citeshttps://doi.org/10.1016/j.jvcir.2023.103831openalex-snapshot
Fast saliency prediction based on multi-channels activation optimization
inferred← citeshttps://doi.org/10.1016/j.jvcir.2025.104676openalex-snapshot
Visual saliency fixation via deeply tri-layered multi blended trans-encoder framework
inferred← citeshttps://doi.org/10.1016/j.neucom.2017.03.018openalex-snapshot
Exploiting inter-image similarity and ensemble of extreme learners for fixation prediction using deep features
inferred← citeshttps://doi.org/10.1016/j.neucom.2019.08.091openalex-snapshot
Coarse-to-fine salient object detection with low-rank matrix recovery
inferred← citeshttps://doi.org/10.1016/j.neucom.2020.06.125openalex-snapshot
Predicting atypical visual saliency for autism spectrum disorder via scale-adaptive inception module and discriminative region enhancement loss
inferred← citeshttps://doi.org/10.1016/j.neucom.2020.06.131openalex-snapshot
Deep saliency models : The quest for the loss function
inferred← citeshttps://doi.org/10.1016/j.neucom.2020.12.011openalex-snapshot
Audiovisual saliency prediction via deep learning
inferred← citeshttps://doi.org/10.1016/j.neucom.2021.07.088openalex-snapshot
Video saliency prediction via spatio-temporal reasoning
inferred← citeshttps://doi.org/10.1016/j.neunet.2020.05.004openalex-snapshot
Contextual encoder–decoder network for visual saliency prediction
inferred← citeshttps://doi.org/10.1016/j.sigpro.2018.01.003openalex-snapshot
Predicting human gaze with multi-level information
inferred← citeshttps://doi.org/10.1038/s41598-023-34829-xopenalex-snapshot
Spatiotemporal bias of the human gaze toward hierarchical visual features during natural scene viewing
inferred← citeshttps://doi.org/10.1038/s44184-023-00031-0openalex-snapshot
A conceptual framework of cognitive-affective theory of mind: towards a precision identification of mental disorders
inferred← citeshttps://doi.org/10.1109/access.2017.2753830openalex-snapshot
Gaze-Assisted Multi-Stream Deep Neural Network for Action Recognition
inferred← citeshttps://doi.org/10.1109/access.2019.2946479openalex-snapshot
Real-Time Video Saliency Prediction Via 3D Residual Convolutional Neural Network
inferred← citeshttps://doi.org/10.1109/apsipaasc47483.2019.9023127openalex-snapshot
Integrating Action-aware Features for Saliency Prediction via Weakly Supervised Learning
inferred← citeshttps://doi.org/10.1109/cchi.2019.8901953openalex-snapshot
Multiple Context Aggregation Network for Saliency Prediction
inferred← citeshttps://doi.org/10.1109/cvpr.2017.123openalex-snapshot
Automatic Understanding of Image and Video Advertisements
inferred← citeshttps://doi.org/10.1109/cvpr.2017.153openalex-snapshot
Deep 360 Pilot: Learning a Deep Agent for Piloting through 360° Sports Videos
inferred← citeshttps://doi.org/10.1109/cvpr.2018.00154openalex-snapshot
Cube Padding for Weakly-Supervised Saliency Prediction in 360° Videos
inferred← citeshttps://doi.org/10.1109/cvpr.2018.00184openalex-snapshot
Salient Object Detection Driven by Fixation Prediction
inferred← citeshttps://doi.org/10.1109/cvpr.2018.00514openalex-snapshot
Revisiting Video Saliency: A Large-Scale Benchmark and a New Model
inferred← citeshttps://doi.org/10.1109/cvpr.2019.01045openalex-snapshot
Understanding and Visualizing Deep Visual Saliency Models
inferred← citeshttps://doi.org/10.1109/cvpr42600.2020.00027openalex-snapshot
Predicting Goal-Directed Human Attention Using Inverse Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/cvpr42600.2020.00482openalex-snapshot
STAViS: Spatio-Temporal AudioVisual Saliency Network
inferred← citeshttps://doi.org/10.1109/cvprw.2018.00269openalex-snapshot
Audio-Visual Temporal Saliency Modeling Validated by fMRI Data
inferred← citeshttps://doi.org/10.1109/cvprw.2019.00109openalex-snapshot
SUSiNet: See, Understand and Summarize It
inferred← citeshttps://doi.org/10.1109/icassp43922.2022.9747003openalex-snapshot
Importantaug: A Data Augmentation Agent for Speech
inferred← citeshttps://doi.org/10.1109/icccnt61001.2024.10726176openalex-snapshot
Scanpath Prediction through Convolutional Neural Network and Feature-Based Clustering: A Bottom-Up Approach
inferred← citeshttps://doi.org/10.1109/iccv.2017.513openalex-snapshot
Understanding Low- and High-Level Contributions to Fixation Prediction
inferred← citeshttps://doi.org/10.1109/iccvw.2017.158openalex-snapshot
Learning Invariant Riemannian Geometric Representations Using Deep Nets
inferred← citeshttps://doi.org/10.1109/iccvw54120.2021.00418openalex-snapshot
Simple baselines can fool 360° saliency metrics
inferred← citeshttps://doi.org/10.1109/icip.2017.8296692openalex-snapshot
Anomaly detection in thermal images using deep neural networks
inferred← citeshttps://doi.org/10.1109/icip.2019.8802611openalex-snapshot
Saliency Detection via Topological Feature Modulated Deep Learning
inferred← citeshttps://doi.org/10.1109/icmew.2017.8026277openalex-snapshot
Visual saliency for image captioning in new multimedia services
inferred← citeshttps://doi.org/10.1109/itnec.2019.8729365openalex-snapshot
Multiscope Contextual Information for Saliency Prediction
inferred← citeshttps://doi.org/10.1109/jsen.2020.3038432openalex-snapshot
Attention-SLAM: A Visual Monocular SLAM Learning From Human Gaze
inferred← citeshttps://doi.org/10.1109/jstsp.2019.2957981openalex-snapshot
Spatial and Temporal Consistency-Aware Dynamic Adaptive Streaming for 360-Degree Videos
inferred← citeshttps://doi.org/10.1109/lra.2020.2998410openalex-snapshot
Using Human Gaze to Improve Robustness Against Irrelevant Objects in Robot Manipulation Tasks
inferred← citeshttps://doi.org/10.1109/lsp.2020.3035065openalex-snapshot
ABSNet: Aesthetics-Based Saliency Network Using Multi-Task Convolutional Network
inferred← citeshttps://doi.org/10.1109/ojemb.2024.3367492openalex-snapshot
Predicting Clinician Fixations on Glaucoma OCT Reports via CNN-Based Saliency Prediction Methods
inferred← citeshttps://doi.org/10.1109/tcds.2021.3094974openalex-snapshot
A Gated Fusion Network for Dynamic Saliency Prediction
inferred← citeshttps://doi.org/10.1109/tcds.2023.3274179openalex-snapshot
SalDA: DeepConvNet Greets Attention for Visual Saliency Prediction
inferred← citeshttps://doi.org/10.1109/tcsvt.2018.2870954openalex-snapshot
Learning Coupled Convolutional Networks Fusion for Video Saliency Prediction
inferred← citeshttps://doi.org/10.1109/tcsvt.2018.2883305openalex-snapshot
Video Saliency Prediction Based on Spatial-Temporal Two-Stream Network
inferred← citeshttps://doi.org/10.1109/tip.2017.2682981openalex-snapshot
RGBD Salient Object Detection via Deep Fusion
inferred← citeshttps://doi.org/10.1109/tip.2017.2767288openalex-snapshot
Saliency Detection Based on Multiscale Extrema of Local Perceptual Color Differences
inferred← citeshttps://doi.org/10.1109/tip.2017.2787612openalex-snapshot
Deep Visual Attention Prediction
inferred← citeshttps://doi.org/10.1109/tip.2018.2817047openalex-snapshot
A Deep Spatial Contextual Long-Term Recurrent Convolutional Network for Saliency Detection
inferred← citeshttps://doi.org/10.1109/tip.2018.2834826openalex-snapshot
Visual Saliency Prediction Using a Mixture of Deep Neural Networks
inferred← citeshttps://doi.org/10.1109/tip.2018.2851672openalex-snapshot
Predicting Human Eye Fixations via an LSTM-Based Saliency Attentive Model
inferred← citeshttps://doi.org/10.1109/tip.2018.2859752openalex-snapshot
Co-Salient Object Detection Based on Deep Saliency Networks and Seed Propagation Over an Integrated Graph
inferred← citeshttps://doi.org/10.1109/tip.2020.3016464openalex-snapshot
Visual Saliency via Embedding Hierarchical Knowledge in a Deep Neural Network
inferred← citeshttps://doi.org/10.1109/tip.2022.3158064openalex-snapshot
Weakly Supervised Visual Saliency Prediction
inferred← citeshttps://doi.org/10.1109/tip.2023.3287137openalex-snapshot
Predictive Uncertainty Estimation for Camouflaged Object Detection
inferred← citeshttps://doi.org/10.1109/tip.2024.3461956openalex-snapshot
How is Visual Attention Influenced by Text Guidance? Database and Model
inferred← citeshttps://doi.org/10.1109/tits.2024.3361903openalex-snapshot
Context-Aware Driver Attention Estimation Using Multi-Hierarchy Saliency Fusion With Gaze Tracking
inferred← citeshttps://doi.org/10.1109/tmi.2023.3273528openalex-snapshot
Laplacian Salience-Gated Feature Pyramid Network for Accurate Liver Vessel Segmentation
inferred← citeshttps://doi.org/10.1109/tmm.2017.2767784openalex-snapshot
Saliency Detection in Face Videos: A Data-Driven Approach
inferred← citeshttps://doi.org/10.1109/tmm.2017.2777665openalex-snapshot
Spatio-Temporal Saliency Networks for Dynamic Saliency Prediction
inferred← citeshttps://doi.org/10.1109/tmm.2018.2851389openalex-snapshot
Improving Saliency Detection Based on Modeling Photographer's Intention
inferred← citeshttps://doi.org/10.1109/tmm.2019.2947352openalex-snapshot
A Dilated Inception Network for Visual Saliency Prediction
inferred← citeshttps://doi.org/10.1109/tmm.2021.3081260openalex-snapshot
Cross-Modality Fusion and Progressive Integration Network for Saliency Prediction on Stereoscopic 3D Images
inferred← citeshttps://doi.org/10.1109/tmm.2021.3139743openalex-snapshot
Spatio-Temporal Self-Attention Network for Video Saliency Prediction
inferred← citeshttps://doi.org/10.1109/tpami.2019.2905607openalex-snapshot
Inferring Salient Objects from Human Fixations
inferred← citeshttps://doi.org/10.1109/tpami.2019.2924417openalex-snapshot
Revisiting Video Saliency Prediction in the Deep Learning Era
inferred← citeshttps://doi.org/10.1109/tpami.2019.2935715openalex-snapshot
Saliency Prediction in the Deep Learning Era: Successes and Limitations
inferred← citeshttps://doi.org/10.1109/tpami.2021.3068277openalex-snapshot
Deep Cognitive Gate: Resembling Human Cognition for Saliency Detection
inferred← citeshttps://doi.org/10.1109/vcip67698.2025.11396834openalex-snapshot
Robust Road Object Detection with CAESAR: Context-Aware Explanations via Semantic Attribution and Refinement
inferred← citeshttps://doi.org/10.1109/vr.2019.8797816openalex-snapshot
Optimizing Visual Element Placement via Visual Attention Analysis
inferred← citeshttps://doi.org/10.1109/vr46266.2020.00027openalex-snapshot
SalBiNet360: Saliency Prediction on 360° Images with Local-Global Bifurcated Deep Network
inferred← citeshttps://doi.org/10.1109/wacv.2017.8openalex-snapshot
Deep Salient Object Detection by Integrating Multi-level Cues
inferred← citeshttps://doi.org/10.1109/wacv.2018.00172openalex-snapshot
Task Specific Visual Saliency Prediction with Memory Augmented Conditional Generative Adversarial Networks
inferred← citeshttps://doi.org/10.1117/1.jei.28.3.033033openalex-snapshot
Evaluation of bottom-up saliency model using deep features pretrained by deep convolutional neural networks
inferred← citeshttps://doi.org/10.1145/3444685.3446304openalex-snapshot
Cross-modal learning for saliency prediction in mobile environment
inferred← citeshttps://doi.org/10.1145/3698881openalex-snapshot
Audio-Visual Saliency Prediction Model with Implicit Neural Representation
inferred← citeshttps://doi.org/10.1145/3810984.3817074openalex-snapshot
EyeSpy: Saliency-Guided Lifelog Retrieval Using Gaze
inferred← citeshttps://doi.org/10.1155/2021/6610997openalex-snapshot
Deep Multimodal Fusion Autoencoder for Saliency Prediction of RGB‐D Images
inferred← citeshttps://doi.org/10.1155/2023/9922475openalex-snapshot
Transparent and Interpretable State of Health Forecasting of Lithium-Ion Batteries with Deep Learning and Saliency Maps
inferred← citeshttps://doi.org/10.1609/aaai.v33i01.33018521openalex-snapshot
Image Saliency Prediction in Transformed Domain: A Deep Complex Neural Network Method
inferred← citeshttps://doi.org/10.21203/rs.3.rs-510910/v1openalex-snapshot
Attention mechanisms and deep learning for machine vision: A survey of the state of the art
inferred← citeshttps://doi.org/10.24963/ijcai.2020/689openalex-snapshot
Human Gaze Assisted Artificial Intelligence: A Review
inferred← citeshttps://doi.org/10.31234/osf.io/s3u9jopenalex-snapshot
What can computational models learn from human selective attention? A review from an audiovisual crossmodal perspective
inferred← citeshttps://doi.org/10.31799/1684-8853-2019-3-10-36openalex-snapshot
Saliency detection in deep learning era: trends of development
inferred← citeshttps://doi.org/10.3233/ia-170033openalex-snapshot
Attentive models in vision: Computing saliency maps in the deep learning era
inferred← citeshttps://doi.org/10.32657/10356/145826openalex-snapshot
Visual saliency computation and quality evaluation via deep learning
inferred← citeshttps://doi.org/10.3389/fnint.2020.00010openalex-snapshot
What Can Computational Models Learn From Human Selective Attention? A Review From an Audiovisual Unimodal and Crossmodal Perspective
inferred← citeshttps://doi.org/10.3390/app12010309openalex-snapshot
Review of Visual Saliency Prediction: Development Process from Neurobiological Basis to Deep Models
inferred← citeshttps://doi.org/10.3390/electronics11081180openalex-snapshot
A Saliency Prediction Model Based on Re-Parameterization and Channel Attention Mechanism
inferred← citeshttps://doi.org/10.3390/sym11010005openalex-snapshot
High Precision Detection of Salient Objects Based on Deep Convolutional Networks with Proper Combinations of Shallow and Deep Connections
inferred← citeshttps://doi.org/10.48550/arxiv.1603.08199openalex-snapshot
Recurrent Mixture Density Network for Spatiotemporal Visual Attention
inferred← citeshttps://doi.org/10.48550/arxiv.1701.01081openalex-snapshot
SalGAN: Visual Saliency Prediction with Generative Adversarial Networks
inferred← citeshttps://doi.org/10.48550/arxiv.1705.01759openalex-snapshot
Deep 360 Pilot: Learning a Deep Agent for Piloting through 360° Sports Video
inferred← citeshttps://doi.org/10.48550/arxiv.1706.08474openalex-snapshot
Paying More Attention to Saliency: Image Captioning with Saliency and Context Attention
inferred← citeshttps://doi.org/10.48550/arxiv.1709.02495openalex-snapshot
DeepFeat: A Bottom Up and Top Down Saliency Model Based on Deep Features of Convolutional Neural Nets
inferred← citeshttps://doi.org/10.48550/arxiv.1803.05753openalex-snapshot
What Catches the Eye? Visualizing and Understanding Deep Saliency Models
inferred← citeshttps://doi.org/10.48550/arxiv.1809.00567openalex-snapshot
PathGAN: Visual Scanpath Prediction with Generative Adversarial Networks
inferred← citeshttps://doi.org/10.48550/arxiv.1810.03716openalex-snapshot
Saliency Prediction in the Deep Learning Era: Successes, Limitations, and Future Challenges
inferred← citeshttps://doi.org/10.48550/arxiv.1901.05002openalex-snapshot
Light-weighted Saliency Detection with Distinctively Lower Memory Cost and Model Size
inferred← citeshttps://doi.org/10.48550/arxiv.2004.04221openalex-snapshot
Saliency-based Weighted Multi-label Linear Discriminant Analysis
inferred← citeshttps://doi.org/10.70675/100cc7d7zae8bz447az8d92z5d9607455e96openalex-snapshot
Indexation bio-inspirée pour la recherche d'images par similarité
inferred← citeshttps://doi.org/10.70675/62992609z895bz4aa6z8f4fzd298df4375fcopenalex-snapshot
Application of Interactive Machine Learning Models For Human-Robot Interaction : the Human Attention Approach
inferred← citeshttps://doi.org/10.7287/peerj-cs.280v0.1/reviews/1openalex-snapshot
Peer Review #1 of "A novel fully convolutional network for visual saliency prediction (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.280v0.1/reviews/2openalex-snapshot
Peer Review #2 of "A novel fully convolutional network for visual saliency prediction (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj-cs.280v0.2/reviews/1openalex-snapshot
Peer Review #1 of "A novel fully convolutional network for visual saliency prediction (v0.2)"
inferred← citeshttps://doi.org/10.7717/peerj-cs.280openalex-snapshot
A novel fully convolutional network for visual saliency prediction
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.