Publications

You can also find my articles on my Google Scholar profile.

Data Augmentation via Latent Diffusion for Saliency Prediction

Published in Proceedings of the European Conference on Computer Vision, 2024

We propose a novel data augmentation method for deep saliency prediction that edits natural images while preserving the complexity and variability of real-world scenes.

Recommended citation: Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang, Mathieu Salzmann, Sabine Süsstrunk. (2024). "Data Augmentation via Latent Diffusion for Saliency Prediction." European Conference on Computer Vision (ECCV).
Download Paper | Download Slides

TempSAL - Uncovering Temporal Information for Deep Saliency Prediction

Published in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

This paper introduces a novel saliency prediction model that learns to output saliency maps in sequential time intervals by exploiting human temporal attention patterns.

Recommended citation: Bahar Aydemir, Ludo Hoffstetter, Tong Zhang, Mathieu Salzmann, Sabine Süsstrunk. (2023). "TempSAL - Uncovering Temporal Information for Deep Saliency Prediction." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 6461-6470.
Download Paper | Download Slides

Modeling Object Dissimilarity for Deep Saliency Prediction

Published in Transactions on Machine Learning Research (TMLR), 2022

We introduce a detection-guided saliency prediction network that explicitly models the differences between multiple objects, such as their appearance and size dissimilarities.

Recommended citation: Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang, Seungryong Kim, Mathieu Salzmann, Sabine Süsstrunk. (2022). " Modeling Object Dissimilarity for Deep Saliency Prediction." Transactions on Machine Learning Research (TMLR).
Download Paper | Download Slides