AIMC Topic: Visual Perception

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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...

Robust visual question answering via polarity enhancement and contrast.

Neural networks : the official journal of the International Neural Network Society
The Visual Question Answering (VQA) task is an important research direction in the field of artificial intelligence, which requires a model that can simultaneously understand visual images and natural language questions, and answer questions related ...

The neural network RTNet exhibits the signatures of human perceptual decision-making.

Nature human behaviour
Convolutional neural networks show promise as models of biological vision. However, their decision behaviour, including the facts that they are deterministic and use equal numbers of computations for easy and difficult stimuli, differs markedly from ...

Factorized visual representations in the primate visual system and deep neural networks.

eLife
Object classification has been proposed as a principal objective of the primate ventral visual stream and has been used as an optimization target for deep neural network models (DNNs) of the visual system. However, visual brain areas represent many d...

A computationally efficient and robust looming perception model based on dynamic neural field.

Neural networks : the official journal of the International Neural Network Society
There are primarily two classes of bio-inspired looming perception visual systems. The first class employs hierarchical neural networks inspired by well-acknowledged anatomical pathways responsible for looming perception, and the second maps nonlinea...

Biological direct-shortcut deep residual learning for sparse visual processing.

Scientific reports
We show, based on the following three grounds, that the primary visual cortex (V1) is a biological direct-shortcut deep residual learning neural network (ResNet) for sparse visual processing: (1) We first highlight that Gabor-like sets of basis funct...

Microsaccade-inspired event camera for robotics.

Science robotics
Neuromorphic vision sensors or event cameras have made the visual perception of extremely low reaction time possible, opening new avenues for high-dynamic robotics applications. These event cameras' output is dependent on both motion and texture. How...

Understanding Human Cognition Through Computational Modeling.

Topics in cognitive science
One important goal of cognitive science is to understand the mind in terms of its representational and computational capacities, where computational modeling plays an essential role in providing theoretical explanations and predictions of human behav...

Computational reconstruction of mental representations using human behavior.

Nature communications
Revealing how the mind represents information is a longstanding goal of cognitive science. However, there is currently no framework for reconstructing the broad range of mental representations that humans possess. Here, we ask participants to indicat...

Do we really need a large number of visual prompts?

Neural networks : the official journal of the International Neural Network Society
Due to increasing interest in adapting models on resource-constrained edges, parameter-efficient transfer learning has been widely explored. Among various methods, Visual Prompt Tuning (VPT), prepending learnable prompts to input space, shows competi...