Making Sense of Real-World Scenes

[1]  Chris I Baker,et al.  Contributions of low- and high-level properties to neural processing of visual scenes in the human brain , 2017, Philosophical Transactions of the Royal Society B: Biological Sciences.

[2]  Dejan Draschkow,et al.  Gist in time: Scene semantics and structure enhance recall of searched objects. , 2016, Acta psychologica.

[3]  Li Fei-Fei,et al.  Two Distinct Scene-Processing Networks Connecting Vision and Memory , 2016, eNeuro.

[4]  C. Baker,et al.  Scene-Selectivity and Retinotopy in Medial Parietal Cortex , 2016, Front. Hum. Neurosci..

[5]  John G. Mikhael,et al.  Functional neuroanatomy of intuitive physical inference , 2016, Proceedings of the National Academy of Sciences.

[6]  Katrina Ferrara,et al.  Neural representation of scene boundaries , 2016, Neuropsychologia.

[7]  Moritz F. Wurm,et al.  What’s she doing in the kitchen? Context helps when actions are hard to recognize , 2016, Psychonomic Bulletin & Review.

[8]  M. Castelo‐Branco,et al.  Distinct preference for spatial frequency content in ventral stream regions underlying the recognition of scenes, faces, bodies and other objects , 2016, Neuropsychologia.

[9]  Antonio Torralba,et al.  Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence , 2016, Scientific Reports.

[10]  Krista A. Ehinger,et al.  When is it time to move to the next map? Optimal foraging in guided visual search , 2016, Attention, Perception, & Psychophysics.

[11]  Russell A. Epstein,et al.  The Occipital Place Area Is Causally Involved in Representing Environmental Boundaries during Navigation , 2016, Current Biology.

[12]  P. Howe,et al.  Failure to detect meaning in RSVP at 27 ms per picture , 2016, Attention, Perception, & Psychophysics.

[13]  Daniel D. Dilks,et al.  Perceived egocentric distance sensitivity and invariance across scene-selective cortex , 2016, Cortex.

[14]  Dwight J. Kravitz,et al.  Evaluating the correspondence between face-, scene-, and object-selectivity and retinotopic organization within lateral occipitotemporal cortex , 2016, Journal of vision.

[15]  Russell A. Epstein,et al.  Rectilinear Edge Selectivity Is Insufficient to Explain the Category Selectivity of the Parahippocampal Place Area , 2016, Front. Hum. Neurosci..

[16]  Richelle L. Witherspoon,et al.  How You Use It Matters , 2016, Psychological science.

[17]  Dirk B. Walther,et al.  Contour junctions underlie neural representations of scene categories in high-level human visual cortex , 2016, NeuroImage.

[18]  J. Mattingley,et al.  Functional Organization of the Parahippocampal Cortex: Dissociable Roles for Context Representations and the Perception of Visual Scenes , 2016, The Journal of Neuroscience.

[19]  J. DiCarlo,et al.  Using goal-driven deep learning models to understand sensory cortex , 2016, Nature Neuroscience.

[20]  V. Lamme,et al.  The time course of natural scene perception with reduced attention. , 2016, Journal of neurophysiology.

[21]  K. R. Ridderinkhof,et al.  Conflict in the kitchen: Contextual modulation of responsiveness to affordances , 2016, Consciousness and Cognition.

[22]  Daniel D. Dilks,et al.  The occipital place area represents the local elements of scenes , 2016, NeuroImage.

[23]  Pienie Zwitserlood,et al.  Rapid apprehension of the coherence of action scenes , 2016, Psychonomic bulletin & review.

[24]  Jonathan S. Cant,et al.  Feature diagnosticity and task context shape activity in human scene-selective cortex , 2016, NeuroImage.

[25]  Russell A. Epstein,et al.  Common Neural Representations for Visually Guided Reorientation and Spatial Imagery , 2016, Cerebral cortex.

[26]  Benjamin W. Tatler,et al.  Looking at Domestic Textiles: An Eye-Tracking Experiment Analysing Influences on Viewing Behaviour at Owlpen Manor , 2016 .

[27]  Tom Hartley,et al.  Patterns of neural response in scene-selective regions of the human brain are affected by low-level manipulations of spatial frequency , 2016, NeuroImage.

[28]  F. W. Mast,et al.  Street crossing behavior in younger and older pedestrians: an eye- and head-tracking study , 2015, BMC Geriatrics.

[29]  Dimitrios Pantazis,et al.  Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks , 2015, NeuroImage.

[30]  Jack L. Gallant,et al.  Fourier power, subjective distance, and object categories all provide plausible models of BOLD responses in scene-selective visual areas , 2015, Front. Comput. Neurosci..

[31]  Russell A. Epstein,et al.  Outside Looking In: Landmark Generalization in the Human Navigational System , 2015, The Journal of Neuroscience.

[32]  N. Kriegeskorte.  Deep neural networks: a new framework for modelling biological vision and brain information processing , 2015, bioRxiv.

[33]  Dwight J. Kravitz,et al.  A Retinotopic Basis for the Division of High-Level Scene Processing between Lateral and Ventral Human Occipitotemporal Cortex , 2015, The Journal of Neuroscience.

[34]  Peter Zeidman,et al.  A central role for the retrosplenial cortex in de novo environmental learning , 2015, eLife.

[35]  Aude Oliva,et al.  Interaction envelope: Local spatial representations of objects at all scales in scene-selective regions , 2015, NeuroImage.

[36]  Nathalie Guyader,et al.  Spatial frequency processing in scene-selective cortical regions , 2015, NeuroImage.

[37]  Bevil R. Conway,et al.  Functional Architecture for Disparity in Macaque Inferior Temporal Cortex and Its Relationship to the Architecture for Faces, Color, Scenes, and Visual Field , 2015, The Journal of Neuroscience.

[38]  George L. Malcolm,et al.  Object-based attention in real-world scenes. , 2015, Journal of experimental psychology. General.

[39]  Michelle R. Greene,et al.  What you see is what you expect: rapid scene understanding benefits from prior experience , 2015, Attention, Perception, & Psychophysics.

[40]  W. Einhäuser,et al.  Annals of the New York Academy of Sciences Issue: Competitive Visual Processing across Space and Time a New Approach to Modeling the Influence of Image Features on Fixation Selection in Scenes , 2022 .

[41]  George L. Malcolm,et al.  Disentangling the effects of spatial inconsistency of targets and distractors when searching in realistic scenes. , 2015, Journal of vision.

[42]  S. Nordin,et al.  Assessing the physical environment of older people’s residential care facilities: development of the Swedish version of the Sheffield Care Environment Assessment Matrix (S-SCEAM) , 2015, BMC Geriatrics.

[43]  A. Khosla,et al.  Object Detectors Emerge in Deep Scene CNNs , 2014, ICLR.

[44]  Bolei Zhou,et al.  Learning Deep Features for Scene Recognition using Places Database , 2014, NIPS.

[45]  M. Pomplun,et al.  The roles of scene gist and spatial dependency among objects in the semantic guidance of attention in real-world scenes , 2014, Vision Research.

[46]  Russell A. Epstein.  Neural Systems for Visual Scene Recognition , 2014 .

[47]  Marcel A. J. van Gerven,et al.  Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream , 2014, The Journal of Neuroscience.

[48]  Michelle R. Greene,et al.  Visual Noise from Natural Scene Statistics Reveals Human Scene Category Representations , 2014, ArXiv.

[49]  Nikolaus Kriegeskorte,et al.  Deep Supervised, but Not Unsupervised, Models May Explain IT Cortical Representation , 2014, PLoS Comput. Biol..

[50]  Russell A. Epstein,et al.  Anchoring the neural compass: Coding of local spatial reference frames in human medial parietal lobe , 2014, Nature Neuroscience.

[51]  Erik Rietveld,et al.  A Rich Landscape of Affordances , 2014 .

[52]  Tom Hartley,et al.  Patterns of response to visual scenes are linked to the low-level properties of the image , 2014, NeuroImage.

[53]  Charles E. Connor,et al.  A Channel for 3D Environmental Shape in Anterior Inferotemporal Cortex , 2014, Neuron.

[54]  Sean P. MacEvoy,et al.  Do Simultaneously Viewed Objects Influence Scene Recognition Individually or as Groups? Two Perceptual Studies , 2014, PloS one.

[55]  Monica S. Castelhano,et al.  Peripheral guidance in scenes: The interaction of scene context and object content. , 2014, Journal of experimental psychology. Human perception and performance.

[56]  Steven G. Luke,et al.  Incidental memory for parts of scenes from eye movements , 2014 .

[57]  J. Wolfe,et al.  Seek and you shall remember: scene semantics interact with visual search to build better memories. , 2014, Journal of vision.

[58]  D. Ballard,et al.  Modeling Task Control of Eye Movements , 2014, Current Biology.

[59]  R. Tootell,et al.  Thinking Outside the Box: Rectilinear Shapes Selectively Activate Scene-Selective Cortex , 2014, The Journal of Neuroscience.

[60]  Ha Hong,et al.  Performance-optimized hierarchical models predict neural responses in higher visual cortex , 2014, Proceedings of the National Academy of Sciences.

[61]  Russell A. Epstein,et al.  Multiple object properties drive scene-selective regions. , 2014, Cerebral cortex.

[62]  Stefan Carlsson,et al.  CNN Features Off-the-Shelf: An Astounding Baseline for Recognition , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

[63]  Philippe G. Schyns,et al.  Beyond Gist , 2014, Psychological science.

[64]  George L. Malcolm,et al.  How context information and target information guide the eyes from the first epoch of search in real-world scenes. , 2014, Journal of vision.

[65]  Russell A. Epstein,et al.  Neural systems for landmark-based wayfinding in humans , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[66]  A. Nuthmann.  How do the regions of the visual field contribute to object search in real-world scenes? Evidence from eye movements. , 2014, Journal of experimental psychology. Human perception and performance.

[67]  Qi Zhao,et al.  Predicting human gaze beyond pixels. , 2014, Journal of vision.

[68]  Dirk B. Walther,et al.  Nonaccidental Properties Underlie Human Categorization of Complex Natural Scenes , 2014, Psychological science.

[69]  Aude Oliva,et al.  Parametric Coding of the Size and Clutter of Natural Scenes in the Human Brain. , 2014, Cerebral cortex.

[70]  M. Potter,et al.  Detecting meaning in RSVP at 13 ms per picture , 2013, Attention, Perception, & Psychophysics.

[71]  Sennay Ghebreab,et al.  From Image Statistics to Scene Gist: Evoked Neural Activity Reveals Transition from Low-Level Natural Image Structure to Scene Category , 2013, The Journal of Neuroscience.

[72]  Jessica B. Hamrick,et al.  Simulation as an engine of physical scene understanding , 2013, Proceedings of the National Academy of Sciences.

[73]  Bevil R. Conway,et al.  Parallel, multi-stage processing of colors, faces and shapes in macaque inferior temporal cortex , 2013, Nature Neuroscience.

[74]  J. Gallant,et al.  Natural Scene Statistics Account for the Representation of Scene Categories in Human Visual Cortex , 2013, Neuron.

[75]  Xueqi Cheng,et al.  A Network for Scene Processing in the Macaque Temporal Lobe , 2013, Neuron.

[76]  M. Bar,et al.  The role of the parahippocampal cortex in cognition , 2013, Trends in Cognitive Sciences.

[77]  George L. Malcolm,et al.  Eye-guidance during scene search: The role color plays in central and peripheral vision , 2013 .

[78]  Fei-Fei Li,et al.  Differential connectivity within the Parahippocampal Place Area , 2013, NeuroImage.

[79]  Weimin Mou,et al.  Defining a boundary in goal localization: Infinite number of points or extended surfaces. , 2013, Journal of experimental psychology. Learning, memory, and cognition.

[80]  Reshanne R. Reeder,et al.  The contents of the search template for category-level search in natural scenes. , 2013, Journal of vision.

[81]  Russell A. Epstein,et al.  Abstract Representations of Location and Facing Direction in the Human Brain , 2013, The Journal of Neuroscience.

[82]  Dwight J. Kravitz,et al.  Deconstructing visual scenes in cortex: gradients of object and spatial layout information. , 2013, Cerebral cortex.

[83]  Maciej Pajak,et al.  Object-based saccadic selection during scene perception: evidence from viewing position effects. , 2013, Journal of vision.

[84]  Bhuvanesh Awasthi,et al.  Distinct spatial scale sensitivities for early categorization of faces and places: neuromagnetic and behavioral findings , 2013, Front. Hum. Neurosci..

[85]  J. Wolfe,et al.  The interplay of episodic and semantic memory in guiding repeated search in scenes , 2013, Cognition.

[86]  D. Newport,et al.  Transient natural convection in a conducting enclosure heated from above , 2013, J. Vis..

[87]  Dwight J. Kravitz,et al.  The ventral visual pathway: an expanded neural framework for the processing of object quality , 2013, Trends in Cognitive Sciences.

[88]  Daniel D. Dilks,et al.  The Occipital Place Area Is Causally and Selectively Involved in Scene Perception , 2013, The Journal of Neuroscience.

[89]  Tom Foulsham,et al.  Optimal and Preferred Eye Landing Positions in Objects and Scenes , 2013, Quarterly journal of experimental psychology.

[90]  Ohad Ben-Shahar,et al.  A perceptual paradigm and psychophysical evidence for hierarchy in scene gist processing. , 2012, Journal of vision.

[91]  Roger B. H. Tootell,et al.  A Cardinal Orientation Bias in Scene-Selective Visual Cortex , 2012, The Journal of Neuroscience.

[92]  Victor A. F. Lamme,et al.  Spatially Pooled Contrast Responses Predict Neural and Perceptual Similarity of Naturalistic Image Categories , 2012, PLoS Comput. Biol..

[93]  Eleanor A. Maguire,et al.  Retrosplenial Cortex Codes for Permanent Landmarks , 2012, PloS one.

[94]  A. Oliva,et al.  A Real-World Size Organization of Object Responses in Occipitotemporal Cortex , 2012, Neuron.

[95]  Jonathan S. Cant,et al.  Object Ensemble Processing in Human Anterior-Medial Ventral Visual Cortex , 2012, The Journal of Neuroscience.

[96]  Curtis L Baker,et al.  Natural versus Synthetic Stimuli for Estimating Receptive Field Models: A Comparison of Predictive Robustness , 2012, The Journal of Neuroscience.

[97]  Simon P. Liversedge,et al.  The effect of the first glimpse at a scene on eye movements during search , 2012, Psychonomic bulletin & review.

[98]  Rufin VanRullen,et al.  Four Common Conceptual Fallacies in Mapping the Time Course of Recognition , 2011, Front. Psychology.

[99]  C. Cierpka,et al.  Particle imaging techniques for volumetric three-component (3D3C) velocity measurements in microfluidics , 2011, Journal of Visualization.

[100]  Moreno I. Coco,et al.  The Interplay of Bottom-Up and Top-Down Mechanisms in Visual Guidance during Object Naming , 2011, Quarterly journal of experimental psychology.

[101]  T. Foulsham,et al.  The where, what and when of gaze allocation in the lab and the natural environment , 2011, Vision Research.

[102]  Miguel P Eckstein,et al.  Object co-occurrence serves as a contextual cue to guide and facilitate visual search in a natural viewing environment. , 2011, Journal of vision.

[103]  Daniel D. Dilks,et al.  Mirror-Image Sensitivity and Invariance in Object and Scene Processing Pathways , 2011, The Journal of Neuroscience.

[104]  Alex D. Hwang,et al.  Semantic guidance of eye movements in real-world scenes , 2011, Vision Research.

[105]  M. Castelhano,et al.  Scene context influences without scene gist: Eye movements guided by spatial associations in visual search , 2011, Psychonomic bulletin & review.

[106]  Eleanor A Maguire,et al.  A New Role for the Parahippocampal Cortex in Representing Space , 2011, The Journal of Neuroscience.

[107]  Dwight J. Kravitz,et al.  Real-World Scene Representations in High-Level Visual Cortex: It's the Spaces More Than the Places , 2011, The Journal of Neuroscience.

[108]  Dirk B. Walther,et al.  Simple line drawings suffice for functional MRI decoding of natural scene categories , 2011, Proceedings of the National Academy of Sciences.

[109]  Natalia Y. Bilenko,et al.  The “Parahippocampal Place Area” Responds Preferentially to High Spatial Frequencies in Humans and Monkeys , 2011, PLoS biology.

[110]  Laura A. Carlson,et al.  Selecting landmarks in novel environments , 2011, Psychonomic bulletin & review.

[111]  Kerry Hourigan,et al.  Wake transition of a rolling sphere , 2011, J. Vis..

[112]  E. Spelke,et al.  Young children reorient by computing layout geometry, not by matching images of the environment , 2011, Psychonomic bulletin & review.

[113]  Soojin Park,et al.  Disentangling Scene Content from Spatial Boundary: Complementary Roles for the Parahippocampal Place Area and Lateral Occipital Complex in Representing Real-World Scenes , 2011, The Journal of Neuroscience.

[114]  Masaaki Kawahashi,et al.  Renovation of Journal of Visualization , 2010, J. Vis..

[115]  Arnold W. M. Smeulders,et al.  A Biologically Plausible Model for Rapid Natural Scene Identification , 2009, NIPS.

[116]  Dirk B. Walther,et al.  Natural Scene Categories Revealed in Distributed Patterns of Activity in the Human Brain , 2009, The Journal of Neuroscience.

[117]  B. Tatler,et al.  The prominence of behavioural biases in eye guidance , 2009 .

[118]  A. Smeulders,et al.  Brain responses strongly correlate with Weibull image statistics when processing natural images. , 2009, Journal of vision.

[119]  Michelle R. Greene,et al.  The Briefest of Glances: The Time Course of Natural Scene Understanding , 2009 .

[120]  Michelle R. Greene,et al.  Recognition of natural scenes from global properties: Seeing the forest without representing the trees , 2009, Cognitive Psychology.

[121]  Michael L. Mack,et al.  Viewing task influences eye movement control during active scene perception. , 2009, Journal of vision.

[122]  J. Henderson,et al.  The influence of color on the perception of scene gist. , 2008, Journal of experimental psychology. Human perception and performance.

[123]  Christian F. Doeller,et al.  Parallel striatal and hippocampal systems for landmarks and boundaries in spatial memory , 2008, Proceedings of the National Academy of Sciences.

[124]  Guillaume A. Rousselet,et al.  Processing scene context: Fast categorization and object interference , 2007, Vision Research.

[125]  B. Stankiewicz,et al.  Acquisition of structural versus object landmark knowledge. , 2007, Journal of experimental psychology. Human perception and performance.

[126]  P. Perona,et al.  What do we perceive in a glance of a real-world scene? , 2007, Journal of vision.

[127]  A. E. Patla,et al.  Gaze fixation patterns for negotiating complex ground terrain , 2007, Neuroscience.

[128]  Mary Hayhoe,et al.  Control of attention and gaze in complex environments. , 2006, Journal of vision.

[129]  R. Baddeley,et al.  The long and the short of it: Spatial statistics at fixation vary with saccade amplitude and task , 2006, Vision Research.

[130]  E. Halgren,et al.  Top-down facilitation of visual recognition. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[131]  Miguel P Eckstein,et al.  Attentional Cues in Real Scenes, Saccadic Targeting, and Bayesian Priors , 2005, Psychological science.

[132]  A. Oliva,et al.  Diagnostic colours contribute to the early stages of scene categorization: Behavioural and neurophysiological evidence , 2005 .

[133]  J. Gallant,et al.  Natural Stimulus Statistics Alter the Receptive Field Structure of V1 Neurons , 2004, The Journal of Neuroscience.

[134]  Jodi L. Davenport,et al.  Scene Consistency in Object and Background Perception , 2004, Psychological science.

[135]  Antonio Torralba,et al.  Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope , 2001, International Journal of Computer Vision.

[136]  A. Oliva,et al.  Diagnostic Colors Mediate Scene Recognition , 2000, Cognitive Psychology.

[137]  A. Oliva,et al.  Coarse Blobs or Fine Edges? Evidence That Information Diagnosticity Changes the Perception of Complex Visual Stimuli , 1997, Cognitive Psychology.

[138]  Daniel R. Montello,et al.  Scale and Multiple Psychologies of Space , 1993, COSIT.

[139]  D J Field,et al.  Relations between the statistics of natural images and the response properties of cortical cells. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[140]  B. Tversky,et al.  Categories of environmental scenes , 1983, Cognitive Psychology.

[141]  J. H. Bertera,et al.  Masking of foveal and parafoveal vision during eye fixations in reading. , 1981, Journal of experimental psychology. Human perception and performance.

[142]  N. Graham.  Does the brain perform a Fourier analysis of the visual scene? , 1979, Trends in Neurosciences.

[143]  Michelle R. Greene,et al.  Visual scenes are categorized by function. , 2016, Journal of experimental psychology. General.

[144]  George L. Malcolm,et al.  Eye guidance during real-world scene search: The role color plays in central and peripheral vision. , 2016, Journal of vision.

[145]  Jeremy M Wolfe,et al.  When is it time to move to the next raspberry bush? Foraging rules in human visual search. , 2013, Journal of vision.

[146]  Masahiro Takei,et al.  Human resource development and visualization , 2009, J. Vis..

[147]  A. Oliva,et al.  Author ' s personal copy The role of context in object recognition , 2007 .

[148]  A. Mizuno,et al.  A change of the leading player in flow Visualization technique , 2006, J. Vis..

[149]  L. Itti,et al.  Modeling the influence of task on attention , 2005, Vision Research.

[150]  Katsumi Aoki,et al.  Recent development of flow visualization , 2004, J. Vis..

[151]  J. Henderson,et al.  High-level scene perception. , 1999, Annual review of psychology.

[152]  J. Gibson.  The Ecological Approach to Visual Perception , 1979 .

[153]  Krista A. Ehinger,et al.  Please Scroll down for Article Visual Cognition Modelling Search for People in 900 Scenes: a Combined Source Model of Eye Guidance , 2022 .