Thomas S.A. Wallis

Cited by

	All	Since 2016
Citations	1031	751
h-index	14	11
i10-index	16	13

240

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200820092010201120122013201420152016201720182019202020218 26 19 47 39 34 50 49 49 112 146 188 223 30

Co-authors

Matthias BethgeTübingen University & Amazon ScholarVerified email at bethgelab.org
Matthias KümmererCentre for integrative Neuroscience, University TuebingenVerified email at bethgelab.org
Leon A. GatysApple Inc.Verified email at bethgelab.org
Derek H. ArnoldSchool of Psychology, The University of QueenslandVerified email at psy.uq.edu.au
Felix WichmannEberhard Karls Universität TübingenVerified email at uni-tuebingen.de
Christina Maria FunkeUniversity of TübingenVerified email at bethgelab.org
Alexander S. EckerUniversity of Göttingen, GermanyVerified email at cs.uni-goettingen.de
Mark HorswillThe University of QueenslandVerified email at psy.uq.edu.au
Judy BorowskiPhD student, University of Tübingen & International Max Planck Research School for Intelligent SystemsVerified email at bethgelab.org
Wieland BrendelPostdoctoral Fellow, University of TübingenVerified email at uni-tuebingen.de
Philip GroveThe University of QueenslandVerified email at psy.uq.edu.au
Michael DorrAdaptive Sensory TechnologyVerified email at tum.de
Christopher Patrick TaylorNew England College of OptometryVerified email at neco.edu
Warrick RoseboomDepartment of Informatics, University of SussexVerified email at sussex.ac.uk
Holly E. ErskineQueensland Centre for Mental Health Research; School of Population Health, University of QueenslandVerified email at qcmhr.uq.edu.au
Luis Andres LesmesPresident, Co-Founder Adaptive Sensory TechnologyVerified email at adaptivesensorytech.com
Claudio MichaelisPhD student, University of TübingenVerified email at uni-tuebingen.de
Roland Simon ZimmermannUniversity of TübingenVerified email at uni-tuebingen.de
Robert GeirhosUniversity of Tübingen & International Max Planck Research School for Intelligent Systems (IMPRS-IS)Verified email at uni-tuebingen.de

Thomas S.A. Wallis

Amazon

Verified email at amazon.com

Vision Science Psychophysics Computational Modeling of Vision Machine Learning Statistics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Understanding low-and high-level contributions to fixation prediction M Kummerer, TSA Wallis, LA Gatys, M Bethge Proceedings of the IEEE International Conference on Computer Vision, 4789-4798, 2017	297*	2017
Using fuzzy signal detection theory to determine why experienced and trained drivers respond faster than novices in a hazard perception test TSA Wallis, MS Horswill Accident Analysis & Prevention 39 (6), 1177-1185, 2007	193	2007
Information-theoretic model comparison unifies saliency metrics M Kümmerer, TSA Wallis, M Bethge Proceedings of the National Academy of Sciences 112 (52), 16054-16059, 2015	113	2015
Motion-induced blindness and motion streak suppression TSA Wallis, DH Arnold Current Biology 19 (4), 325-329, 2009	47	2009
Staying focused: A functional account of perceptual suppression during binocular rivalry DH Arnold, PM Grove, TSA Wallis Journal of Vision 7 (7), 7-7, 2007	45	2007
A parametric texture model based on deep convolutional features closely matches texture appearance for humans TSA Wallis, CM Funke, AS Ecker, LA Gatys, FA Wichmann, M Bethge Journal of vision 17 (12), 5-5, 2017	38	2017
Testing models of peripheral encoding using metamerism in an oddity paradigm TSA Wallis, M Bethge, FA Wichmann Journal of vision 16 (2), 4-4, 2016	37	2016
Visual crowding is correlated with awareness TSA Wallis, PJ Bex Current Biology 21 (3), 254-258, 2011	35	2011
Binocular switch suppression: A new method for persistently rendering the visible ‘invisible’ DH Arnold, P Law, TSA Wallis Vision research 48 (8), 994-1001, 2008	33	2008
Saliency benchmarking made easy: Separating models, maps and metrics M Kummerer, TSA Wallis, M Bethge Proceedings of the European Conference on Computer Vision (ECCV), 770-787, 2018	31	2018
Image correlates of crowding in natural scenes TSA Wallis, PJ Bex Journal of Vision 12 (7), 6: 1--19, 2012	30	2012
Motion-induced blindness is not tuned to retinal speed TSA Wallis, DH Arnold Journal of Vision 8 (2), 11-11, 2008	25	2008
Perceived size and spatial coding DH Arnold, A Birt, TSA Wallis Journal of Neuroscience 28 (23), 5954-5958, 2008	20	2008
Image content is more important than Bouma’s Law for scene metamers TSA Wallis, CM Funke, AS Ecker, LA Gatys, FA Wichmann, M Bethge ELife 8, e42512, 2019	16	2019
The notorious difficulty of comparing human and machine perception CM Funke, J Borowski, K Stosio, W Brendel, TSA Wallis, M Bethge arXiv preprint arXiv:2004.09406, 2020	14*	2020
Characterization of field loss based on microperimetry is predictive of face recognition difficulties TSA Wallis, CP Taylor, J Wallis, ML Jackson, PJ Bex Investigative ophthalmology & visual science 55 (1), 142-153, 2014	11	2014
Spatiotemporal rivalry: A perceptual conflict involving illusory moving and static forms DH Arnold, HE Erskine, W Roseboom, TSA Wallis Psychological Science 21 (5), 692-699, 2010	8	2010
Guiding human gaze with convolutional neural networks LA Gatys, M Kümmerer, TSA Wallis, M Bethge arXiv preprint arXiv:1712.06492, 2017	6	2017
Saliency benchmarking: Separating models, maps and metrics M Kümmerer, TS Wallis, M Bethge arXiv preprint arXiv:1704.08615, 2017	6	2017
Meaning maps and saliency models based on deep convolutional neural networks are insensitive to image meaning when predicting human fixations MA Pedziwiatr, M Kümmerer, TSA Wallis, M Bethge, C Teufel Cognition 206, 104465, 2021	4	2021

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