{"total":17,"rows":[{"id":"2108.05479","title":"Automatic Gaze Analysis: A Survey of Deep Learning based Approaches","created":"2021-08-12","cited_by_count":33,"area":null},{"id":"2103.13922","title":"ScanGAN360: A Generative Model of Realistic Scanpaths for 360$^{\\circ}$ Images","created":"2021-03-25","cited_by_count":23,"area":null},{"id":"2303.09383","title":"Unifying Top-down and Bottom-up Scanpath Prediction Using Transformers","created":"2023-03-16","cited_by_count":22,"area":null},{"id":"2304.10784","title":"Eyettention: An Attention-based Dual-Sequence Model for Predicting Human Scanpaths during Reading","created":"2023-04-21","cited_by_count":19,"area":null},{"id":"2204.09093","title":"Behind the Machine's Gaze: Neural Networks with Biologically-inspired Constraints Exhibit Human-like Visual Attention","created":"2022-04-19","cited_by_count":7,"area":null},{"id":"2207.04250","title":"Improving saliency models' predictions of the next fixation with humans' intrinsic cost of gaze shifts","created":"2022-07-09","cited_by_count":4,"area":null},{"id":"2410.23409","title":"TPP-Gaze: Modelling Gaze Dynamics in Space and Time with Neural Temporal Point Processes","created":"2024-10-30","cited_by_count":4,"area":null},{"id":"2204.09404","title":"A Probabilistic Time-Evolving Approach to Scanpath Prediction","created":"2022-04-20","cited_by_count":2,"area":null},{"id":"2212.10367","title":"Modeling Human Eye Movements with Neural Networks in a Maze-Solving Task","created":"2022-12-20","cited_by_count":2,"area":null},{"id":"2405.08981","title":"Impact of Design Decisions in Scanpath Modeling","created":"2024-05-14","cited_by_count":2,"area":null},{"id":"2507.18503","title":"Human Scanpath Prediction in Target-Present Visual Search with Semantic-Foveal Bayesian Attention","created":"2025-07-24","cited_by_count":2,"area":null},{"id":"2404.10836","title":"Semantic-Based Active Perception for Humanoid Visual Tasks with Foveal Sensors","created":"2024-04-16","cited_by_count":1,"area":null},{"id":"2405.02929","title":"Unified Dynamic Scanpath Predictors Outperform Individually Trained Neural Models","created":"2024-05-05","cited_by_count":1,"area":null},{"id":"2506.02764","title":"Unified Attention Modeling for Efficient Free-Viewing and Visual Search via Shared Representations","created":"2025-06-03","cited_by_count":1,"area":null},{"id":"2607.02083","title":"DeepGaze3.5-VL: Modeling Scanpaths via Autoregressive Token Prediction","created":"2026-07-02","cited_by_count":1,"area":null},{"id":"2503.08531","title":"Visual Attention Graph","created":"2025-03-11","cited_by_count":0,"area":null},{"id":"2508.18404","title":"Saccade crossing avoidance as a visual search strategy","created":"2025-08-25","cited_by_count":0,"area":null}],"next_cursor":null}