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The process through which humans perceive and learn visual representations in dynamic environments is highly complex. From a structural perspective, the human eye decouples the functions of cone and rod cells: cones are primarily…

Computer Vision and Pattern Recognition · Computer Science 2025-10-02 Gaole Dai , Menghang Dong , Rongyu Zhang , Ruichuan An , Shanghang Zhang , Tiejun Huang

When selective attention is devoted to one of multiple stimuli within receptive fields of neurons in visual area V4, cells respond as if only the attended stimulus was present. The underlying neural mechanisms are still debated, but…

Neurons and Cognition · Quantitative Biology 2023-05-25 Lukas-Paul Rausch , Maik Schünemann , Eric Drebitz , Daniel Harnack , Udo A. Ernst , Andreas K. Kreiter

The occurrence of a critical period of plasticity in the visual cortex has long been established, yet its function in normal development is not fully understood. Here we show that as the late phase of the critical period unfolds, different…

Neurons and Cognition · Quantitative Biology 2015-05-13 Matthias Kaschube , Michael Schnabel , Siegrid Löwel , Fred Wolf

The human visual system is an intricate network of brain regions that enables us to recognize the world around us. Despite its abundant lateral and feedback connections, object processing is commonly viewed and studied as a feedforward…

Neurons and Cognition · Quantitative Biology 2019-10-09 Tim C Kietzmann , Courtney J Spoerer , Lynn Sörensen , Radoslaw M Cichy , Olaf Hauk , Nikolaus Kriegeskorte

Chart understanding requires models to effectively analyze and reason about numerical data, textual elements, and complex visual components. Our observations reveal that the perception capabilities of existing large vision-language models…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Junteng Liu , Weihao Zeng , Xiwen Zhang , Yijun Wang , Zifei Shan , Junxian He

In studying primate vision, a large body of work focuses on the first feedforward sweep. During this initial time window, information is thought to pass through ventral stream regions in a stage-like fashion in an effort to extract…

Neurons and Cognition · Quantitative Biology 2026-04-15 Daniel Anthes , Sushrut Thorat , Anna Mitola , Paolo Papale , Peter König , Tim C Kietzmann

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

The visual information in V1 is processed by an array of modules called orientation preference columns. In some species including humans, orientation columns are radially arranged around singular points like the spokes of a wheel, that are…

Mathematical Physics · Physics 2010-07-09 Davide Barbieri , Giovanna Citti , Gonzalo Sanguinetti , Alessandro Sarti

Vision-Language Models (VLMs) have shown remarkable progress in visual understanding in recent years. Yet, they still lag behind human capabilities in specific visual tasks such as counting or relational reasoning. To understand the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Zihan Weng , Lucas Gomez , Taylor Whittington Webb , Pouya Bashivan

Deep neural perception and control networks are likely to be a key component of self-driving vehicles. These models need to be explainable - they should provide easy-to-interpret rationales for their behavior - so that passengers, insurance…

Computer Vision and Pattern Recognition · Computer Science 2017-04-03 Jinkyu Kim , John Canny

Vision Transformers, ViTs, have emerged as a powerful alternative to convolutional neural networks, CNNs, in a variety of image-based tasks. While CNNs have previously been evaluated for their ability to perform graphical perception tasks,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-23 Poonam Poonam , Pere-Pau Vázquez , Timo Ropinski

Transformer, first applied to the field of natural language processing, is a type of deep neural network mainly based on the self-attention mechanism. Thanks to its strong representation capabilities, researchers are looking at ways to…

Computer Vision and Pattern Recognition · Computer Science 2023-07-11 Kai Han , Yunhe Wang , Hanting Chen , Xinghao Chen , Jianyuan Guo , Zhenhua Liu , Yehui Tang , An Xiao , Chunjing Xu , Yixing Xu , Zhaohui Yang , Yiman Zhang , Dacheng Tao

Elucidating the functional mechanisms of the primary visual cortex (V1) remains a fundamental challenge in systems neuroscience. Current computational models face two critical limitations, namely the challenge of cross-modal integration…

Neurons and Cognition · Quantitative Biology 2024-12-20 Yu Zhu , Bo Lei , Chunfeng Song , Wanli Ouyang , Shan Yu , Tiejun Huang

The use of Vision-Language Models (VLMs) in automated driving applications is becoming increasingly common, with the aim of leveraging their reasoning and generalisation capabilities to handle long tail scenarios. However, these models…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Nikos Theodoridis , Reenu Mohandas , Ganesh Sistu , Anthony Scanlan , Ciarán Eising , Tim Brophy

Neural decoding, the process of understanding how brain activity corresponds to different stimuli, has been a primary objective in cognitive sciences. Over the past three decades, advances in functional Magnetic Resonance Imaging (fMRI) and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Yanchen Wang , Adam Turnbull , Tiange Xiang , Yunlong Xu , Sa Zhou , Adnan Masoud , Shekoofeh Azizi , Feng Vankee Lin , Ehsan Adeli

Large vision-language models exhibit inherent capabilities to handle diverse visual perception tasks. In this paper, we introduce VisionReasoner, a unified framework capable of reasoning and solving multiple visual perception tasks within a…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Yuqi Liu , Tianyuan Qu , Zhisheng Zhong , Bohao Peng , Shu Liu , Bei Yu , Jiaya Jia

Top-down attention allows neural networks, both artificial and biological, to focus on the information most relevant for a given task. This is known to enhance performance in visual perception. But it remains unclear how attention brings…

Computer Vision and Pattern Recognition · Computer Science 2021-06-23 Freddie Bickford Smith , Brett D Roads , Xiaoliang Luo , Bradley C Love

Visual priming is known to affect the human visual system to allow detection of scene elements, even those that may have been near unnoticeable before, such as the presence of camouflaged animals. This process has been shown to be an effect…

Computer Vision and Pattern Recognition · Computer Science 2017-11-20 Amir Rosenfeld , Mahdi Biparva , John K. Tsotsos

The Human visual perception of the world is of a large fixed image that is highly detailed and sharp. However, receptor density in the retina is not uniform: a small central region called the fovea is very dense and exhibits high…

Computer Vision and Pattern Recognition · Computer Science 2017-01-26 Alon Hazan , Yuval Harel , Ron Meir

Visual Saliency refers to the innate human mechanism of focusing on and extracting important features from the observed environment. Recently, there has been a notable surge of interest in the field of automotive research regarding the…

Computer Vision and Pattern Recognition · Computer Science 2023-08-09 Francesco Rundo , Michael Sebastian Rundo , Concetto Spampinato
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