# TempSAL -- Uncovering Temporal Information for Deep Saliency Prediction

arXiv: https://arxiv.org/abs/2301.02315 · HTML: https://mlsanity.com/paper/2301.02315/

## Key facts

- Cited by 25 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 55 references that are in the map.
- First posted on arXiv 5 Jan 2023.

## Builds on (most cited first, 22 of 22)

- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://mlsanity.com/paper/1409.1556/) (2014)
- [Feature Pyramid Networks for Object Detection](https://mlsanity.com/paper/1612.03144/) (2016)
- [Progressive Neural Architecture Search](https://mlsanity.com/paper/1712.00559/) (2017)
- [What do different evaluation metrics tell us about saliency models?](https://mlsanity.com/paper/1604.03605/) (2016)
- [Salient Object Detection in the Deep Learning Era: An In-Depth Survey](https://mlsanity.com/paper/1904.09146/) (2019)
- [Predicting Human Eye Fixations via an LSTM-based Saliency Attentive Model](https://mlsanity.com/paper/1611.09571/) (2016)
- [Unified Image and Video Saliency Modeling](https://mlsanity.com/paper/2003.05477/) (2020)
- [Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet](https://mlsanity.com/paper/1411.1045/) (2014)
- [DeepGaze IIE: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling](https://mlsanity.com/paper/2105.12441/) (2021)
- [A Deep Multi-Level Network for Saliency Prediction](https://mlsanity.com/paper/1609.01064/) (2016)
- [CAT2000: A Large Scale Fixation Dataset for Boosting Saliency Research](https://mlsanity.com/paper/1505.03581/) (2015)
- [EML-NET:An Expandable Multi-Layer NETwork for Saliency Prediction](https://mlsanity.com/paper/1805.01047/) (2018)
- [Contextual Encoder-Decoder Network for Visual Saliency Prediction](https://mlsanity.com/paper/1902.06634/) (2019)
- [Predicting Visual Importance Across Graphic Design Types](https://mlsanity.com/paper/2008.02912/) (2020)
- [A Deep Spatial Contextual Long-term Recurrent Convolutional Network for Saliency Detection](https://mlsanity.com/paper/1610.01708/) (2016)
- [A Dilated Inception Network for Visual Saliency Prediction](https://mlsanity.com/paper/1904.03571/) (2019)
- [Tidying Deep Saliency Prediction Architectures](https://mlsanity.com/paper/2003.04942/) (2020)
- [Saliency Prediction with External Knowledge](https://mlsanity.com/paper/2007.13839/) (2020)
- [RecSal : Deep Recursive Supervision for Visual Saliency Prediction](https://mlsanity.com/paper/2008.13745/) (2020)
- [Modeling Object Dissimilarity for Deep Saliency Prediction](https://mlsanity.com/paper/2104.03864/) (2021)

## Built on by (most cited first, 25 of 25)

- [GazeXplain: Learning to Predict Natural Language Explanations of Visual Scanpaths](https://mlsanity.com/paper/2408.02788/) (2024)
- [Beyond Average: Individualized Visual Scanpath Prediction](https://mlsanity.com/paper/2404.12235/) (2024)
- [SUM: Saliency Unification through Mamba for Visual Attention Modeling](https://mlsanity.com/paper/2406.17815/) (2024)
- [Trends, Applications, and Challenges in Human Attention Modelling](https://mlsanity.com/paper/2402.18673/) (2024)
- [How is Visual Attention Influenced by Text Guidance? Database and Model](https://mlsanity.com/paper/2404.07537/) (2024)
- [Brand Visibility in Packaging: A Deep Learning Approach for Logo Detection, Saliency-Map Prediction, and Logo Placement Analysis](https://mlsanity.com/paper/2403.02336/) (2024)
- [Data Augmentation via Latent Diffusion for Saliency Prediction](https://mlsanity.com/paper/2409.07307/) (2024)
- [Modeling Saliency Dataset Bias](https://mlsanity.com/paper/2505.10169/) (2025)
- [Measuring and Predicting Where and When Pathologists Focus their Visual Attention while Grading Whole Slide Images of Cancer](https://mlsanity.com/paper/2508.01668/) (2025)
- [FS-Diff: Semantic guidance and clarity-aware simultaneous multimodal image fusion and super-resolution](https://mlsanity.com/paper/2509.09427/) (2025)
- [Integrating Cognitive Processing Signals into Language Models: A Review of Advances, Applications and Future Directions](https://mlsanity.com/paper/2504.06843/) (2025)
- [Enhancing Saliency Prediction in Monitoring Tasks: The Role of Visual Highlights](https://mlsanity.com/paper/2405.09695/) (2024)
- [SalNAS: Efficient Saliency-prediction Neural Architecture Search with self-knowledge distillation](https://mlsanity.com/paper/2407.20062/) (2024)
- [Aligning XAI with EU Regulations for Smart Biomedical Devices: A Methodology for Compliance Analysis](https://mlsanity.com/paper/2408.15121/) (2024)
- [Unlocking Comics: The AI4VA Dataset for Visual Understanding](https://mlsanity.com/paper/2410.20459/) (2024)
- [DTFSal: Audio-Visual Dynamic Token Fusion for Video Saliency Prediction](https://mlsanity.com/paper/2504.10070/) (2025)
- [Attend to Anything: Foundation Model for Unified Human Attention Modeling](https://mlsanity.com/paper/2606.03540/) (2026)
- [DeepGaze3.5-VL: Modeling Scanpaths via Autoregressive Token Prediction](https://mlsanity.com/paper/2607.02083/) (2026)
- [A Comparative Study of Scanpath Models in Graph-Based Visualization](https://mlsanity.com/paper/2503.24160/) (2025)
- [PRE-MAP: Personalized Reinforced Eye-tracking Multimodal LLM for High-Resolution Multi-Attribute Point Prediction](https://mlsanity.com/paper/2507.19213/) (2025)
- [Controllable Audio-Visual Viewpoint Generation from 360deg Spatial Information](https://mlsanity.com/paper/2510.06060/) (2025)
- [EgoCampus: Egocentric Pedestrian Eye Gaze Model and Dataset](https://mlsanity.com/paper/2512.07668/) (2025)
- [ObjectVisA-120: Object-based Visual Attention Prediction in Interactive Street-crossing Environments](https://mlsanity.com/paper/2601.13218/) (2026)
- [Intelligent support for Human Oversight: Integrating Reinforcement Learning with Gaze Simulation to Personalize Highlighting](https://mlsanity.com/paper/2602.08403/) (2026)
- [OpenVAM: Open-World Visual Attention Modeling with VLMs](https://mlsanity.com/paper/2609.31364/) (2026)

## Abstract (arXiv)

Deep saliency prediction algorithms complement the object recognition features, they typically rely on additional information, such as scene context, semantic relationships, gaze direction, and object dissimilarity. However, none of these models consider the temporal nature of gaze shifts during image observation. We introduce a novel saliency prediction model that learns to output saliency maps in sequential time intervals by exploiting human temporal attention patterns. Our approach locally modulates the saliency predictions by combining the learned temporal maps. Our experiments show that our method outperforms the state-of-the-art models, including a multi-duration saliency model, on the SALICON benchmark. Our code will be publicly available on GitHub.