How close are we to understanding image-based saliency? - Matthias Kümmerer; Thomas Wallis 001; Matthias Bethge (CoRR, 2014)

Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet. - Matthias Kümmerer; Lucas Theis; Matthias Bethge (ICLR (Workshop), 2015)

DeepGaze II: Reading fixations from deep features trained on object recognition. - Matthias Kümmerer; Thomas S. A. Wallis; Matthias Bethge (CoRR, 2016)

Understanding Low- and High-Level Contributions to Fixation Prediction. - Matthias Kümmerer; Thomas S. A. Wallis; Leon A. Gatys; Matthias Bethge (ICCV, 2017)

Saliency Benchmarking: Separating Models, Maps and Metrics. - Matthias Kümmerer; Thomas S. A. Wallis; Matthias Bethge (CoRR, 2017)

Guiding human gaze with convolutional neural networks. - Leon A. Gatys; Matthias Kümmerer; Thomas S. A. Wallis; Matthias Bethge (CoRR, 2017)

Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics. - Matthias Kümmerer; Thomas S. A. Wallis; Matthias Bethge (ECCV (16), 2018)

Accurate, reliable and fast robustness evaluation. - Wieland Brendel; Jonas Rauber; Matthias Kümmerer; Ivan Ustyuzhaninov; Matthias Bethge (NeurIPS, 2019)

Measuring the Importance of Temporal Features in Video Saliency. - Matthias Tangemann; Matthias Kümmerer; Thomas S. A. Wallis; Matthias Bethge (ECCV (28), 2020)

How well can we predict where people look in images? - Matthias Kümmerer (2020)

DeepGaze IIE: Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling. - Akis Linardos; Matthias Kümmerer; Ori Press; Matthias Bethge (ICCV, 2021)

State-of-the-Art in Human Scanpath Prediction. - Matthias Kümmerer; Matthias Bethge (CoRR, 2021)

Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling. - Akis Linardos; Matthias Kümmerer; Ori Press; Matthias Bethge (CoRR, 2021)

Disentanglement and Generalization Under Correlation Shifts. - Christina M. Funke; Paul Vicol; Kuan-Chieh Wang; Matthias Kümmerer; Richard S. Zemel; Matthias Bethge (CoLLAs, 2022)

Unsupervised Object Learning via Common Fate. - Matthias Tangemann; Steffen Schneider 001; Julius von Kügelgen; Francesco Locatello; Peter Vincent Gehler; Thomas Brox; Matthias Kümmerer; Matthias Bethge; Bernhard Schölkopf (CLeaR, 2023)

RDumb: A simple approach that questions our progress in continual test-time adaptation. - Ori Press; Steffen Schneider 001; Matthias Kümmerer; Matthias Bethge (NeurIPS, 2023)

Object segmentation from common fate: Motion energy processing enables human-like zero-shot generalization to random dot stimuli. - Matthias Tangemann; Matthias Kümmerer; Matthias Bethge (NeurIPS, 2024)

Scale Learning in Scale-Equivariant Convolutional Networks. - Mark Basting; Robert-Jan Bruintjes; Thaddäus Wiedemer; Matthias Kümmerer; Matthias Bethge; Jan van Gemert (VISIGRAPP (2): VISAPP, 2024)

Modeling Saliency Dataset Bias. - Matthias Kümmerer; Harneet Khanuja; Matthias Bethge (CoRR, 2025)