Crowding asymmetries explained by a model of image segmentation

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Publications associées (31)

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Over the last decades, implantable neural interfaces have been extensively explored and effectively deployed to address neurological and mental health disorders. The existing solutions present several limitations. Firstly, the physical size of the implanta ...

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Knowing where objects are relative to us implies knowing where we are relative to the external world. Here, we investigated whether space perception can be influenced by an experimentally induced change in perceived self-location. To dissociate real and ap ...

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The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption

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The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Te ...

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A Stepwise Domain Adaptive Segmentation Network With Covariate Shift Alleviation for Remote Sensing Imagery

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Semantic segmentation for remote sensing images (RSI) is critical for the Earth monitoring system. However, the covariate shift between RSI datasets under different capture conditions cannot be alleviated by directly using the unsupervised domain adaptatio ...

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MultiMAE: Multi-modal Multi-task Masked Autoencoders

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We propose a pre-training strategy called Multi-modal Multi-task Masked Autoencoders (MultiMAE). It differs from standard Masked Autoencoding in two key aspects: I) it can optionally accept additional modalities of information in the input besides the RGB ...

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Object Priors for Volumetric Image Segmentation

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Large training datasets have played a vital role in the success of modern deep learning methods in computer vision. But, obtaining sufficient amount of training data is challenging, specially when annotating volumetric images. This is because fully annotat ...

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Introduction Recent work has shown an association between cognitive and visual impairments and two main theories were advanced, namely the sensory deprivation and the common cause theories. Most studies considered only basic visual functions such as visual ...

2023

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Technological progress in materials science and microengineering along with new discoveries in neuroscience have contributed to restore lost or impaired sensory functions by closely interfacing with the nervous system. Electronic devices have begun to be i ...

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Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

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Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...

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Predicting visual stimuli from cortical response recorded with widefield imaging in a mouse

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Optic nerve stimulation holds great potential for visual prostheses. Its effectiveness depends on the stimulation protocol, which can be optimized to achieve cortical activation similar to that evoked in response to visual stimuli. To identify a target cor ...

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During the Artificial Intelligence (AI) revolution of the past decades, deep neural networks have been widely used and have achieved tremendous success in visual recognition. Unfortunately, deploying deep models is challenging because of their huge model s ...

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