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Visual Perception

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Using machine learning to predict judgments on Western visual art along content-representational and formal-perceptual attributes.

PloS one
Art research has long aimed to unravel the complex associations between specific attributes, such as color, complexity, and emotional expressiveness, and art judgments, including beauty, creativity, and liking. However, the fundamental distinction be...

IdeNet: Making Neural Network Identify Camouflaged Objects Like Creatures.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Camouflaged objects often blend in with their surroundings, making the perception of a camouflaged object a more complex procedure. However, most neural-network-based methods that simulate the visual information processing pathway of creatures only r...

A Multi-Group Multi-Stream attribute Attention network for fine-grained zero-shot learning.

Neural networks : the official journal of the International Neural Network Society
Fine-grained visual categorization in zero-shot setting is a challenging problem in the computer vision community. It requires algorithms to accurately identify fine-grained categories that do not appear during the training phase and have high visual...

Multi-view scene matching with relation aware feature perception.

Neural networks : the official journal of the International Neural Network Society
For scene matching, the extraction of metric features is a challenging task in the face of multi-source and multi-view scenes. Aiming at the requirements of multi-source and multi-view scene matching, a siamese network model for Spatial Relation Awar...

DiagSWin: A multi-scale vision transformer with diagonal-shaped windows for object detection and segmentation.

Neural networks : the official journal of the International Neural Network Society
Recently, Vision Transformer and its variants have demonstrated remarkable performance on various computer vision tasks, thanks to its competence in capturing global visual dependencies through self-attention. However, global self-attention suffers f...

Manipulating and measuring variation in deep neural network (DNN) representations of objects.

Cognition
We explore how DNNs can be used to develop a computational understanding of individual differences in high-level visual cognition given their ability to generate rich meaningful object representations informed by their architecture, experience, and t...

SmartDetector: Automatic and vision-based approach to point-light display generation for human action perception.

Behavior research methods
Over the past four decades, point-light displays (PLD) have been integrated into psychology and psychophysics, providing a valuable means to probe human perceptual skills. Leveraging the inherent kinematic information and controllable display paramet...

Human Eyes-Inspired Recurrent Neural Networks Are More Robust Against Adversarial Noises.

Neural computation
Humans actively observe the visual surroundings by focusing on salient objects and ignoring trivial details. However, computer vision models based on convolutional neural networks (CNN) often analyze visual input all at once through a single feedforw...

Exploring refined dual visual features cross-combination for image captioning.

Neural networks : the official journal of the International Neural Network Society
For current image caption tasks used to encode region features and grid features Transformer-based encoders have become commonplace, because of their multi-head self-attention mechanism, the encoder can better capture the relationship between differe...

A developmental model of audio-visual attention (MAVA) for bimodal language learning in infants and robots.

Scientific reports
A social individual needs to effectively manage the amount of complex information in his or her environment relative to his or her own purpose to obtain relevant information. This paper presents a neural architecture aiming to reproduce attention mec...