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https://github.com/aimagelab/awesome-human-visual-attention
This repository contains a curated list of research papers and resources focusing on saliency and scanpath prediction, human attention, human visual search.
https://github.com/aimagelab/awesome-human-visual-attention
List: awesome-human-visual-attention
Last synced: 11 days ago
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This repository contains a curated list of research papers and resources focusing on saliency and scanpath prediction, human attention, human visual search.
- Host: GitHub
- URL: https://github.com/aimagelab/awesome-human-visual-attention
- Owner: aimagelab
- Created: 2024-01-31T09:53:13.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-08-04T21:11:04.000Z (3 months ago)
- Last Synced: 2024-08-29T10:43:28.218Z (3 months ago)
- Size: 1.01 MB
- Stars: 29
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Human Visual Attention [](https://awesome.re)
This repository contains a curated list of research papers and resources focusing on saliency and scanpath prediction, human attention, human visual search.
❗ Latest Update: 10 September 2024.
❗This repo is a work in progress. New updates coming soon, stay tuned!! :construction:
## 📣 Latest News 📣
- **`20 April 2024`** Our survey paper has been accepted for publication at **IJCAI2024 Survey Track**!
## Our Survey on Human Visual Attention 👀
🔥🔥 [*Trends, Applications, and Challenges in Human Attention Modelling*](http://arxiv.org/abs/2402.18673) 🔥🔥\
\
**Authors:**
[**Giuseppe Cartella**](https://scholar.google.com/citations?hl=en&user=0sJ4VCcAAAAJ),
[**Marcella Cornia**](https://scholar.google.com/citations?user=DzgmSJEAAAAJ&hl=it&oi=ao),
[**Vittorio Cuculo**](https://scholar.google.com/citations?user=usEfqxoAAAAJ&hl=it&oi=ao),
[**Alessandro D'Amelio**](https://scholar.google.com/citations?user=chkawtoAAAAJ&hl=it&oi=ao),
[**Dario Zanca**](https://scholar.google.com/citations?user=KjwaSXkAAAAJ&hl=it&oi=ao),
[**Giuseppe Boccignone**](https://scholar.google.com/citations?user=LqM0uJwAAAAJ&hl=it&oi=ao),
[**Rita Cucchiara**](https://scholar.google.com/citations?user=OM3sZEoAAAAJ&hl=it&oi=ao)
# 📚 Table of Contents
- **Human Attention Modelling**
-
Saliency Prediction
| **Year** | **Conference / Journal** | **Title** | **Authors** | **Links** |
|:--------:|:--------------:|:----------------------------------------------------|:---------------------|:---------:|
| 2025 | WACV | SUM: Saliency Unification through Mamba for Visual Attention Modeling | *Alireza Hosseini et al.* | [📜 Paper](https://arxiv.org/pdf/2406.17815) / [Code :octocat:](https://github.com/Arhosseini77/SUM) / [Project Page](https://arhosseini77.github.io/sum_page/)
| 2024 | WACV | Learning Saliency from Fixations | *Yasser Abdelaziz Dahou Djilali et al.* | [📜 Paper](https://arxiv.org/pdf/2311.14073.pdf) / [Code :octocat:](https://github.com/YasserdahouML/SalTR)
| 2023 | CVPR | Learning from Unique Perspectives: User-aware Saliency Modeling | *Shi Chen et al.* | [📜 Paper](https://openaccess.thecvf.com//content/CVPR2023/papers/Chen_Learning_From_Unique_Perspectives_User-Aware_Saliency_Modeling_CVPR_2023_paper.pdf)
| 2023 | CVPR | TempSAL - Uncovering Temporal Information for Deep Saliency Prediction | *Bahar Aydemir et al.* | [📜 Paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Aydemir_TempSAL_-_Uncovering_Temporal_Information_for_Deep_Saliency_Prediction_CVPR_2023_paper.pdf) / [Code :octocat:](https://github.com/IVRL/Tempsal)
| 2023 | BMVC | Clustered Saliency Prediction | *Rezvan Sherkat et al.* | [📜 Paper](https://arxiv.org/pdf/2207.02205.pdf)
| 2023 | NeurIPS | What Do Deep Saliency Models Learn about Visual Attention? | *Shi Chen et al.* | [📜 Paper](https://arxiv.org/pdf/2310.09679.pdf) / [Code :octocat:](https://github.com/szzexpoi/saliency_analysis)
| 2022 | Neurocomputing | TranSalNet: Towards perceptually relevant visual saliency prediction | *Jianxun Lou et al.* | [📜 Paper](https://www.sciencedirect.com/science/article/pii/S0925231222004714?via%3Dihub) / [Code :octocat:](https://github.com/LJOVO/TranSalNet?tab=readme-ov-file)
| 2020 | CVPR | STAViS: Spatio-Temporal AudioVisual Saliency Network | *Antigoni Tsiami et al.* | [📜 Paper](https://arxiv.org/pdf/2001.03063.pdf) / [Code :octocat:](https://github.com/atsiami/STAViS)
| 2020 | CVPR | How much time do you have? Modeling multi-duration saliency | *Camilo Fosco et al.* | [📜 Paper](https://openaccess.thecvf.com/content_CVPR_2020/papers/Fosco_How_Much_Time_Do_You_Have_Modeling_Multi-Duration_Saliency_CVPR_2020_paper.pdf) / [Code :octocat:](https://github.com/diviz-mit/multiduration-saliency/) / [Project Page](http://multiduration-saliency.csail.mit.edu/)
| 2018 | IEEE Transactions on Image Processing | Predicting Human Eye Fixations via an LSTM-based Saliency Attentive Model | *Marcella Cornia et al.* | [📜 Paper](https://arxiv.org/pdf/1611.09571.pdf) / [Code :octocat:](https://github.com/marcellacornia/sam)
| 2015 | CVPR | SALICON: Saliency in Context | *Ming Jiang et al.* | [📜 Paper](https://openaccess.thecvf.com/content_cvpr_2015/papers/Jiang_SALICON_Saliency_in_2015_CVPR_paper.pdf) / [Project Page](http://salicon.net/)
| 2009 | ICCV | Learning to Predict Where Humans Look | *Tilke Judd et al.* | [📜 Paper](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5459462)
| 1998 | TPAMI | A Model of Saliency-Based Visual Attention for Rapid Scene Analysis | *Laurent Itti et al.* | [📜 Paper](https://forums.cs.tau.ac.il/~hezy/Vision%20Seminar/koch%20attention%20pami.pdf)
-
Scanpath Prediction
| **Year** | **Conference / Journal** | **Title** | **Authors** | **Links** |
|:--------:|:--------------:|:---------:|:-----------:|:---------:|
| 2024 | ECCV | GazeXplain: Learning to Predict Natural Language Explanations of Visual Scanpaths | *Xianyu Chen et al.* | [📜 Paper] / [Code :octocat:](https://github.com/chenxy99/GazeXplain)
| 2024 | ECCV | Look Hear: Gaze Prediction for Speech-directed Human Attention | *Sounak Mondal et al.* | [📜 Paper](https://arxiv.org/pdf/2407.19605) / [Code :octocat:](https://github.com/cvlab-stonybrook/ART)
| 2024 | CVPR | Beyond Average: Individualized Visual Scanpath Prediction | *Xianyu Chen et al.* | [📜 Paper](https://arxiv.org/pdf/2404.12235.pdf)
| 2024 | CVPR | Unifying Top-down and Bottom-up Scanpath Prediction Using Transformers | *Zhibo Yang et al.* | [📜 Paper](https://arxiv.org/pdf/2303.09383.pdf) / [Code :octocat:](https://github.com/cvlab-stonybrook/HAT)
| 2023 | arXiv | Contrastive Language-Image Pretrained Models are Zero-Shot Human Scanpath Predictors | *Dario Zanca et al.* | [📜 Paper](https://arxiv.org/pdf/2305.12380.pdf) / [Code + Dataset :octocat:](https://github.com/mad-lab-fau/CapMIT1003)
| 2023 | CVPR | Gazeformer: Scalable, Effective and Fast Prediction of Goal-Directed Human Attention | *Sounak Mondal et al.* | [📜 Paper](https://arxiv.org/pdf/2303.15274.pdf) / [Code :octocat:](https://github.com/cvlab-stonybrook/Gazeformer/)
| 2022 | ECCV | Target-absent Human Attention | *Zhibo Yang et al.* | [📜 Paper](https://arxiv.org/pdf/2207.01166.pdf) / [Code :octocat:](https://github.com/cvlab-stonybrook/Target-absent-Human-Attention)
| 2022 | TMLR | Behind the Machine's Gaze: Neural Networks with Biologically-inspired Constraints Exhibit Human-like Visual Attention | *Leo Schwinn et al.* | [📜 Paper](https://openreview.net/pdf?id=7iSYW1FRWA) / [Code :octocat:](https://github.com/SchwinnL/NeVA)
| 2022 | Journal of Vision | DeepGaze III: Modeling free-viewing human scanpaths with deep learning | *Matthias Kümmerer et al.* | [📜 Paper](https://jov.arvojournals.org/article.aspx?articleid=2778776) / [Code :octocat:](https://github.com/matthias-k/DeepGaze)
| 2021 | CVPR | Predicting Human Scanpaths in Visual Question Answering | *Xianyu Chen et al.* | [📜 Paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Chen_Predicting_Human_Scanpaths_in_Visual_Question_Answering_CVPR_2021_paper.pdf) / [Code :octocat:](https://github.com/chenxy99/Scanpaths)
| 2019 | TPAMI | Gravitational Laws of Focus of Attention | *Dario Zanca et al.* | [📜 Paper](https://ieeexplore.ieee.org/abstract/document/8730418) / [Code :octocat:](https://github.com/dariozanca/G-Eymol)
| 2015 | Vision Research | Saccadic model of eye movements for free-viewing condition | *Olivier Le Meur et al.* | [📜 Paper](https://www.sciencedirect.com/science/article/pii/S0042698915000504)
- **Integrating Human Attention in AI models**
- ***Image and Video Processing***
-
Visual Recognition
| **Year** | **Conference / Journal** | **Title** | **Authors** | **Links** |
|:--------:|:--------------:|:---------:|:-----------:|:---------:|
| 2023 | IJCV | Joint Learning of Visual-Audio Saliency Prediction and Sound Source Localization on Multi-face Videos | *Minglang Qiao et al.* | [📜 Paper](https://link.springer.com/article/10.1007/s11263-023-01950-3) / [Code :octocat:](https://github.com/MinglangQiao/MVVA-Database?tab=readme-ov-file)
| 2022 | ECML PKDD | Foveated Neural Computation | *Matteo Tiezzi et al.* | [📜 Paper](https://2022.ecmlpkdd.org/wp-content/uploads/2022/09/sub_620.pdf) / [Code :octocat:](https://github.com/sailab-code/foveated_neural_computation)
| 2021 | WACV | Integrating Human Gaze into Attention for Egocentric Activity Recognition | *Kyle Min et al.* | [📜 Paper](https://openaccess.thecvf.com/content/WACV2021/papers/Min_Integrating_Human_Gaze_Into_Attention_for_Egocentric_Activity_Recognition_WACV_2021_paper.pdf) / [Code :octocat:](https://github.com/MichiganCOG/Gaze-Attention)
| 2019 | CVPR | Learning Unsupervised Video Object Segmentation through Visual Attention | *Wenguan Wang et al.* | [📜 Paper](https://openaccess.thecvf.com/content_CVPR_2019/papers/Wang_Learning_Unsupervised_Video_Object_Segmentation_Through_Visual_Attention_CVPR_2019_paper.pdf) / [Code :octocat:](https://github.com/wenguanwang/AGS)
| 2019 | CVPR | Shifting more attention to video salient object detection | *Deng-Ping Fan et al.* | [📜 Paper](https://openaccess.thecvf.com/content_CVPR_2019/papers/Fan_Shifting_More_Attention_to_Video_Salient_Object_Detection_CVPR_2019_paper.pdf) / [Code :octocat:](https://github.com/DengPingFan/DAVSOD)
-
Graphic Design
| **Year** | **Conference / Journal** | **Title** | **Authors** | **Links** |
|:--------:|:--------------:|:---------:|:-----------:|:---------:|
| 2020 | ACM Symposium on UIST (User Interface Software and Technology) | Predicting Visual Importance Across Graphic Design Types | *Camilo Fosco et al.* | [📜 Paper](https://arxiv.org/pdf/2008.02912.pdf) / [Code :octocat:](https://github.com/diviz-mit/predimportance-public)
| 2020 | ACM MobileHCI | Understanding Visual Saliency in Mobile User Interfaces | *Luis A. Leiva et al.* | [📜 Paper](https://arxiv.org/pdf/2101.09176.pdf)
| 2017 | ACM Symposium on UIST (User Interface Software and Technology) | Learning Visual Importance for Graphic Designs and Data Visualizations | *Zoya Bylinskii et al.* | [📜 Paper](https://arxiv.org/pdf/1708.02660.pdf) / [Code :octocat:](https://github.com/cvzoya/visimportance)
-
Image Enhancement and Manipulation
| **Year** | **Conference / Journal** | **Title** | **Authors** | **Links** |
|:--------:|:--------------:|:---------:|:-----------:|:---------:|
| 2023 | CVPR | Realistic saliency guided image enhancement | *S. Mahdi H. Miangoleh et al.* | [📜 Paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Miangoleh_Realistic_Saliency_Guided_Image_Enhancement_CVPR_2023_paper.pdf) / [Code :octocat:](https://github.com/compphoto/RealisticImageEnhancement) / [Project Page](https://yaksoy.github.io/realisticEditing/)
| 2022 | CVPR | Deep saliency prior for reducing visual distraction | *Kfir Aberman et al.* | [📜 Paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Aberman_Deep_Saliency_Prior_for_Reducing_Visual_Distraction_CVPR_2022_paper.pdf) / [Project Page](https://deep-saliency-prior.github.io/)
| 2021 | CVPR | Saliency-guided image translation | *Lai Jiang et al.* | [📜 Paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Jiang_Saliency-Guided_Image_Translation_CVPR_2021_paper.pdf)
| 2017 | arXiv | Guiding human gaze with convolutional neural networks | *Leon A. Gatys et al.* | [📜 Paper](https://arxiv.org/pdf/1712.06492.pdf)
-
Image Quality Assessment
| **Year** | **Conference / Journal** | **Title** | **Authors** | **Links** |
|:--------:|:--------------:|:---------:|:-----------:|:---------:|
| 2023 | CVPR | ScanDMM: A Deep Markov Model of Scanpath Prediction for 360° Images | *Xiangjie Sui et al.* | [📜 Paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Sui_ScanDMM_A_Deep_Markov_Model_of_Scanpath_Prediction_for_360deg_CVPR_2023_paper.pdf) / [Code :octocat:](https://github.com/xiangjieSui/ScanDMM)
| 2021 | ICCV Workshops | Saliency-Guided Transformer Network combined with Local Embedding for No-Reference Image Quality Assessment | *Mengmeng Zhu et al.* | [📜 Paper](https://openaccess.thecvf.com/content/ICCV2021W/AIM/papers/Zhu_Saliency-Guided_Transformer_Network_Combined_With_Local_Embedding_for_No-Reference_Image_ICCVW_2021_paper.pdf)
| 2019 | ACMMM | SGDNet: An End-to-End Saliency-Guided Deep Neural Network for No-Reference Image Quality Assessment | *Sheng Yang et al.* | [📜 Paper](https://dl.acm.org/doi/pdf/10.1145/3343031.3350990) / [Code :octocat:](https://github.com/ysyscool/SGDNet)
- ***Vision-and-Language Applications***
-
Automatic Captioning
| **Year** | **Conference / Journal** | **Title** | **Authors** | **Links** |
|:--------:|:--------------:|:---------:|:-----------:|:---------:|
| 2020 | EMNLP | Generating Image Descriptions via Sequential Cross-Modal Alignment Guided by Human Gaze | *Ece Takmaz et al.* | [📜 Paper](https://aclanthology.org/2020.emnlp-main.377.pdf) / [Code :octocat:](https://github.com/dmg-illc/didec-seq-gen)
| 2019 | ICCV | Human Attention in Image Captioning: Dataset and Analysis | *Sen He et al.* | [📜 Paper](https://openaccess.thecvf.com/content_ICCV_2019/papers/He_Human_Attention_in_Image_Captioning_Dataset_and_Analysis_ICCV_2019_paper.pdf) / [Code :octocat:](https://github.com/SenHe/Human-Attention-in-Image-Captioning)
| 2018 | ACM TOMM | Paying More Attention to Saliency: Image Captioning with Saliency and Context Attention | *Marcella Cornia et al.* | [📜 Paper](https://arxiv.org/pdf/1706.08474.pdf)
| 2017 | CVPR | Supervising Neural Attention Models for Video Captioning by Human Gaze Data | *Youngjae Yu et al.* | [📜 Paper](https://openaccess.thecvf.com/content_cvpr_2017/papers/Yu_Supervising_Neural_Attention_CVPR_2017_paper.pdf) / [Code :octocat:](https://github.com/yj-yu/Recurrent_Gaze_Prediction)
| 2016 | arXiv | Seeing with Humans: Gaze-Assisted Neural Image Captioning | *Yusuke Sugano et al.* | [📜 Paper](https://arxiv.org/pdf/1608.05203.pdf)
-
Visual Question Answering
| **Year** | **Conference / Journal** | **Title** | **Authors** | **Links** |
|:--------:|:--------------:|:---------:|:-----------:|:---------:|
| 2023 | EMNLP | GazeVQA: A Video Question Answering Dataset for Multiview Eye-Gaze Task-Oriented Collaborations | *Muhammet Furkan Ilaslan et al.* | [📜 Paper](https://aclanthology.org/2023.emnlp-main.648.pdf) / [Code :octocat:](https://github.com/mfurkanilaslan/GazeVQA)
| 2023 | CVPR Workshops | Multimodal Integration of Human-Like Attention in Visual Question Answering | *Ekta Sood et al.* | [📜 Paper](https://openaccess.thecvf.com/content/CVPR2023W/GAZE/papers/Sood_Multimodal_Integration_of_Human-Like_Attention_in_Visual_Question_Answering_CVPRW_2023_paper.pdf) / [Project Page](https://perceptualui.org/publications/sood23_gaze/)
| 2021 | CoNLL | VQA-MHUG: A Gaze Dataset to Study Multimodal Neural Attention in Visual Question Answering | *Ekta Sood et al.* | [📜 Paper](https://aclanthology.org/2021.conll-1.3.pdf) / [Dataset + Project Page](https://perceptualui.org/publications/sood21_conll/)
| 2020 | ECCV | AiR: Attention with Reasoning Capability | *Shi Chen et al.* | [📜 Paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123460086.pdf) / [Code :octocat:](https://github.com/szzexpoi/AiR)
| 2018 | AAAI | Exploring Human-like Attention Supervision in Visual Question Answering | *Tingting Qiao et al.* | [📜 Paper](https://arxiv.org/pdf/1709.06308.pdf) / [Code :octocat:](https://github.com/qiaott/HAN)
| 2016 | EMNLP | Human Attention in Visual Question Answering: Do Humans and Deep Networks Look at the Same Regions? | *Abhishek Das et al.* | [📜 Paper](https://aclanthology.org/D16-1092.pdf)
- ***Language Modelling***
-
Machine Reading Comprehension
| **Year** | **Conference / Journal** | **Title** | **Authors** | **Links** |
|:--------:|:--------------:|:---------:|:-----------:|:---------:|
| 2023 | ACL Workshops | Native Language Prediction from Gaze: a Reproducibility Study | *Lina Skerath et al.* | [📜 Paper](https://aclanthology.org/2023.acl-srw.26.pdf) / [Code :octocat:](https://github.com/linaskerath/ANLP_project)
| 2022 | ETRA | Inferring Native and Non-Native Human Reading Comprehension and Subjective Text Difficulty from Scanpaths | *David R. Reich et al.* | [📜 Paper](https://dl.acm.org/doi/pdf/10.1145/3517031.3529639) / [Code :octocat:](https://github.com/aeye-lab/etra-reading-comprehension)
| 2017 | ACL | Predicting Native Language from Gaze | *Yevgeni Berzak et al.* | [📜 Paper](https://aclanthology.org/P17-1050.pdf)
-
Natural Language Understanding
| **Year** | **Conference / Journal** | **Title** | **Authors** | **Links** |
|:--------:|:--------------:|:---------:|:-----------:|:---------:|
| 2023 | EMNLP | Pre-Trained Language Models Augmented with Synthetic Scanpaths for Natural Language Understanding | *Shuwen Deng et al.* | [📜 Paper](https://aclanthology.org/2023.emnlp-main.400.pdf) / [Code :octocat:](https://github.com/aeye-lab/EMNLP-SyntheticScanpaths-NLU-PretrainedLM)
| 2023 | EACL | Synthesizing Human Gaze Feedback for Improved NLP Performance | *Varun Khurana et al.* | [📜 Paper](https://aclanthology.org/2023.eacl-main.139.pdf)
| 2020 | NeurIPS | Improving Natural Language Processing Tasks with Human Gaze-Guided Neural Attention | *Ekta Sood et al.* | [📜 Paper](https://proceedings.neurips.cc/paper_files/paper/2020/file/460191c72f67e90150a093b4585e7eb4-Paper.pdf) / [Project Page](https://perceptualui.org/publications/sood20_neurips/)
- ***Domain-Specific Applications***
-
Robotics
| **Year** | **Conference / Journal** | **Title** | **Authors** | **Links** |
|:--------:|:--------------:|:---------:|:-----------:|:---------:|
| 2023 | IEEE RA-L | GVGNet: Gaze-Directed Visual Grounding for Learning Under-Specified Object Referring Intention | *Kun Qian et al.* | [📜 Paper](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10202186)
| 2022 | RSS | Gaze Complements Control Input for Goal Prediction During Assisted Teleoperation | *Reuben M. Aronson et al.* | [📜 Paper](https://harp.ri.cmu.edu/assets/pubs/aronson_gaze_to_goal_rss22.pdf)
| 2019 | CoRL | Understanding Teacher Gaze Patterns for Robot Learning | *Akanksha Saran et al.* | [📜 Paper](https://proceedings.mlr.press/v100/saran20a/saran20a.pdf) / [Code :octocat:](https://github.com/asaran/gaze-LfD)
| 2019 | CoRL | Nonverbal Robot Feedback for Human Teachers | *Sandy H. Huang et al.* | [📜 Paper](https://proceedings.mlr.press/v100/huang20a/huang20a.pdf)
-
Autonomous Driving
| **Year** | **Conference / Journal** | **Title** | **Authors** | **Links** |
|:--------:|:--------------:|:---------:|:-----------:|:---------:|
| 2023 | ICCV | FBLNet: FeedBack Loop Network for Driver Attention Prediction | *Yilong Chen et al.* | [📜 Paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Chen_FBLNet_FeedBack_Loop_Network_for_Driver_Attention_Prediction_ICCV_2023_paper.pdf)
| 2022 | IEEE Transactions on Intelligent Transportation Systems | DADA: Driver Attention Prediction in Driving Accident Scenarios | *Jianwu Fang et al.* | [📜 Paper](https://arxiv.org/pdf/1912.12148.pdf) / [Code :octocat:](https://github.com/JWFangit/LOTVS-DADA)
| 2021 | ICCV | MEDIRL: Predicting the Visual Attention of Drivers via Deep Inverse Reinforcement Learning | *Sonia Baee et al.* | [📜 Paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Baee_MEDIRL_Predicting_the_Visual_Attention_of_Drivers_via_Maximum_Entropy_ICCV_2021_paper.pdf) / [Code :octocat:](https://github.com/soniabaee/MEDIRL-EyeCar) / [Project Page](https://soniabaee.github.io/projects/medirl-eyecar/medirl-eyecar.html)
| 2020 | CVPR | “Looking at the right stuff” - Guided semantic-gaze for autonomous driving | *Anwesan Pal et al.* | [📜 Paper](https://openaccess.thecvf.com/content_CVPR_2020/papers/Pal_Looking_at_the_Right_Stuff_-_Guided_Semantic-Gaze_for_Autonomous_CVPR_2020_paper.pdf) / [Code :octocat:](https://github.com/anwesanpal/SAGENet_demo)
| 2019 | ITSC | DADA-2000: Can Driving Accident be Predicted by Driver Attention? Analyzed by A Benchmark | *Jianwu Fang et al.* | [📜 Paper](https://arxiv.org/pdf/1904.12634.pdf) / [Code :octocat:](https://github.com/JWFangit/LOTVS-DADA)
| 2018 | ACCV | Predicting Driver Attention in Critical Situations | *Ye Xia et al.* | [📜 Paper](https://arxiv.org/pdf/1711.06406.pdf) / [Code :octocat:](https://github.com/pascalxia/driver_attention_prediction)
| 2018 | TPAMI | Predicting the Driver’s Focus of Attention: the DR(eye)VE Project | *Andrea Palazzi et al.* | [📜 Paper](https://arxiv.org/pdf/1705.03854.pdf) / [Code :octocat:](https://github.com/ndrplz/dreyeve)
-
Medicine
| **Year** | **Conference / Journal** | **Title** | **Authors** | **Links** |
|:--------:|:--------------:|:---------:|:-----------:|:---------:|
| 2024 | MICCAI | Weakly-supervised Medical Image Segmentation with Gaze Annotations | *Yuan Zhong et al.* | [📜 Paper](https://arxiv.org/pdf/2407.07406) / [Code :octocat:](https://github.com/med-air/GazeMedSeg)
| 2024 | AAAI | Mining Gaze for Contrastive Learning toward Computer-Assisted Diagnosis | *Zihao Zhao et al.* | [📜 Paper](https://arxiv.org/pdf/2312.06069.pdf) / [Code :octocat:](https://github.com/zhaozh10/McGIP)
| 2024 | WACV | GazeGNN: A Gaze-Guided Graph Neural Network for Chest X-ray Classification | *Bin Wang et al.* | [📜 Paper](https://openaccess.thecvf.com/content/WACV2024/papers/Wang_GazeGNN_A_Gaze-Guided_Graph_Neural_Network_for_Chest_X-Ray_Classification_WACV_2024_paper.pdf) / [Code :octocat:](https://github.com/ukaukaaaa/GazeGNN)
| 2023 | WACV | Probabilistic Integration of Object Level Annotations in Chest X-ray Classification | *Tom van Sonsbeek et al.* | [📜 Paper](https://openaccess.thecvf.com/content/WACV2023/papers/van_Sonsbeek_Probabilistic_Integration_of_Object_Level_Annotations_in_Chest_X-Ray_Classification_WACV_2023_paper.pdf)
| 2023 | IEEE Transactions on Medical Imaging | Eye-gaze-guided Vision Transformer for Rectifying Shortcut Learning | *Chong Ma et al.* | [📜 Paper](https://arxiv.org/pdf/2205.12466.pdf)
| 2023 | Transactions on Neural Networks and Learning Systems | Rectify ViT Shortcut Learning by Visual Saliency | *Chong Ma et al.* | [📜 Paper](https://ieeexplore.ieee.org/document/10250856)
| 2022 | IEEE Transactions on Medical Imaging | Follow My Eye: Using Gaze to Supervise Computer-Aided Diagnosis | *Sheng Wang et al.* | [📜 Paper](https://arxiv.org/pdf/2204.02976.pdf) / [Code :octocat:](https://github.com/JamesQFreeman/MICEYE)
| 2022 | MICCAI | GazeRadar: A Gaze and Radiomics-Guided Disease Localization Framework | *Moinak Bhattacharya et al.* | [📜 Paper](https://bmi.stonybrookmedicine.edu/sites/default/files/A-Gaze-and-Radiomics-Guided-Disease-Localization-Framework.pdf) / [Code :octocat:](https://github.com/bmi-imaginelab/gazeradar)
| 2022 | ECCV | RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention–guided Disease Classification | *Moinak Bhattacharya et al.* | [📜 Paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136810669.pdf) / [Code :octocat:](https://github.com/bmi-imaginelab/radiotransformer)
| 2021 | Nature Scientific Data | Creation and validation of a chest X-ray dataset with eye-tracking and report dictation for AI development | *Alexandros Karargyris et al.* | [📜 Paper](https://www.nature.com/articles/s41597-021-00863-5) / [Code :octocat:](https://github.com/cxr-eye-gaze/eye-gaze-dataset)
| 2021 | BMVC | Human Attention in Fine-grained Classification | *Yao Rong et al.* | [📜 Paper](https://www.bmvc2021-virtualconference.com/assets/papers/0421.pdf) / [Code :octocat:](https://github.com/yaorong0921/CUB-GHA)
| 2018 | Journal of Medical Imaging | Modeling visual search behavior of breast radiologists using a deep convolution neural network | *Suneeta Mall et al.* | [📜 Paper](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6086967/pdf/JMI-005-035502.pdf)
- **Datasets & Benchmarks 📂📎**
-
Datasets
- [SALICON](http://salicon.net/download/) - [SALICON API](https://github.com/NUS-VIP/salicon-api)
- [MIT1003](https://people.csail.mit.edu/tjudd/WherePeopleLook/index.html)
- [OSIE](https://www-users.cse.umn.edu/~qzhao/predicting.html)
- [COCOFreeView](https://sites.google.com/view/cocosearch/coco-freeview)
- [COCOSearch18](https://sites.google.com/view/cocosearch/)
- [RefCOCO-Gaze](https://github.com/cvlab-stonybrook/refcoco-gaze)
# How to Contribute 🚀
1. Fork this repository and clone it locally.
2. Create a new branch for your changes: `git checkout -b feature-name`.
3. Make your changes and commit them: `git commit -m 'Description of the changes'`.
4. Push to your fork: `git push origin feature-name`.
5. Open a pull request on the original repository by providing a description of your changes.
This project is in constant development, and we welcome contributions to include the latest research papers in the field or report issues 💥💥.