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The power of neural networks lies in their ability to generalize to unseen data, yet the underlying reasons for this phenomenon remain elusive. Numerous rigorous attempts have been made to explain generalization, but available bounds are…

Machine Learning · Computer Science 2021-11-17 W. Ronny Huang , Zeyad Emam , Micah Goldblum , Liam Fowl , J. K. Terry , Furong Huang , Tom Goldstein

What is an image and how to extract latent features? Convolutional Networks (ConvNets) consider an image as organized pixels in a rectangular shape and extract features via convolutional operation in local region; Vision Transformers (ViTs)…

Computer Vision and Pattern Recognition · Computer Science 2023-03-03 Xu Ma , Yuqian Zhou , Huan Wang , Can Qin , Bin Sun , Chang Liu , Yun Fu

Discovered as an apparent pattern, a universal relation between geometry and information called the holographic principle has yet to be explained. This relation is unfolded in the present paper. As it is demonstrated there, the origin of…

General Physics · Physics 2024-07-23 Arkady Bolotin

Why is it that we can recognize object identity and 3D shape from line drawings, even though they do not exist in the natural world? This paper hypothesizes that the human visual system perceives line drawings as if they were approximately…

Computer Vision and Pattern Recognition · Computer Science 2020-04-14 Aaron Hertzmann

Visual illusions may be explained by the likelihood of patches in real-world images, as argued by input-driven paradigms in Neuro-Science. However, neither the data nor the tools existed in the past to extensively support these…

Computer Vision and Pattern Recognition · Computer Science 2020-10-23 Elad Hirsch , Ayellet Tal

The challenge in learning abstract concepts from images in an unsupervised fashion lies in the required integration of visual perception and generalizable relational reasoning. Moreover, the unsupervised nature of this task makes it…

Artificial Intelligence · Computer Science 2024-07-09 Antonia Wüst , Wolfgang Stammer , Quentin Delfosse , Devendra Singh Dhami , Kristian Kersting

This paper makes the case that a powerful new discipline, which we term perception engineering, is steadily emerging. It follows from a progression of ideas that involve creating illusions, from historical paintings and film, to video games…

This article combines the vocabulary of semiotics and category theory to provide a formal analysis of visualization. It shows how familiar processes of visualization fit the semiotic frameworks of both Saussure and Peirce, and extends these…

Logic in Computer Science · Computer Science 2013-11-21 Paul Vickers , Joe Faith , Nick Rossiter

Visual translation tolerance refers to our capacity to recognize objects over a wide range of different retinal locations. Although translation is perhaps the simplest spatial transform that the visual system needs to cope with, the extent…

Neurons and Cognition · Quantitative Biology 2020-12-09 Ryan Blything , Valerio Biscione , Ivan I. Vankov , Casimir J. H. Ludwig , Jeffrey S. Bowers

Many surface cues support three-dimensional shape perception, but people can sometimes still see shape when these features are missing -- in extreme cases, even when an object is completely occluded, as when covered with a draped cloth. We…

Neurons and Cognition · Quantitative Biology 2023-01-11 Ilker Yildirim , Max H. Siegel , Amir A. Soltani , Shraman Ray Chaudhari , Joshua B. Tenenbaum

Information Visualization techniques are built on a context with many factors related to both vision and cognition, making it difficult to draw a clear picture of how data visually turns into comprehension. In the intent of promoting a…

Graphics · Computer Science 2016-05-16 Jose Rodrigues-Jr , Luciana Zaina , Maria Oliveira , Bruno Brandoli , Agma Traina

Graphical perception studies typically measure visualization encoding effectiveness using the error of an "average observer", leading to canonical rankings of encodings for numerical attributes: e.g., position > area > angle > volume. Yet…

Human-Computer Interaction · Computer Science 2022-12-22 Russell Davis , Xiaoying Pu , Yiren Ding , Brian D. Hall , Karen Bonilla , Mi Feng , Matthew Kay , Lane Harrison

Humans learn powerful representations of objects and scenes by observing how they evolve over time. Yet, outside of specific tasks that require explicit temporal understanding, static image pretraining remains the dominant paradigm for…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Nikhil Parthasarathy , S. M. Ali Eslami , João Carreira , Olivier J. Hénaff

In this paper we start with a simple question, how is it possible that humans can recognize different movements over skin with only a prior visual experience of them? Or in general, what is the representation of spatial sequences that are…

Artificial Intelligence · Computer Science 2023-11-14 Viacheslav M. Osaulenko

In physics, there is the prevailing intuition that we are part of a unique external world, and that the goal of physics is to understand and describe this world. This assumption of the fundamentality of objective reality is often seen as a…

Quantum Physics · Physics 2019-07-22 Markus P. Mueller

Most of computer vision focuses on what is in an image. We propose to train a standalone object-centric context representation to perform the opposite task: seeing what is not there. Given an image, our context model can predict where…

Computer Vision and Pattern Recognition · Computer Science 2017-02-28 Jin Sun , David W. Jacobs

Human visual perception is a complex, dynamic and fluctuating process. In addition to the incoming visual stimulus, it is affected by many other factors including temporal context, both external and internal to the observer. In this study…

Neurons and Cognition · Quantitative Biology 2020-07-01 Urit Gordon , Shimon Marom , Naama Brenner

We have a lot of relation to the encoding and the Theory of Information, when considering thinking. This is a natural process and, at once, the complex thing we investigate. This always was a challenge - to understand how our mind works,…

Artificial Intelligence · Computer Science 2012-12-27 Kirill A. Sorudeykin

The aim of this paper is to study the relevance of simplicity and its formal representation as Kolmogorov or algorithmic complexity in the cognitive sciences. The discussion is based on two premises: 1) all human experience is generated in…

General Physics · Physics 2009-06-20 Giulio Ruffini

Understanding of the phenomena of vision and thought require clarification of the general mechanism of perception. So far, philosophical inquiries and scientific investigations have not been able to address clearly the mysteries surrounding…

Neurons and Cognition · Quantitative Biology 2019-09-16 Jahan N. Schad
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