Subjects learned to classify perceptual stimuli varying along continuous, separable dimensions into rule-described categories. The categories were designed to contrast the predictions of a selective-attention exemplar model and a simple rule-based model formalizing an economy-of-description view. Converging evidence about categorization strategies was obtained by also collecting identification ...

This paper studies the influence of adverse listening conditions on exemplar effects in priming experiments that do not instruct participants to use their episodic memories. We conducted two lexical decision experiments, in which a prime and a target represented the same word type and could be spoken by the same or a different speaker. In Experiment 1, participants listened to clear speech, and...

The goal of exemplar-based texture synthesis is to generate images that are visually similar a given exemplar. Recently, promising results have been reported by methods relying on convolutional neural networks (ConvNets) pretrained large-scale image datasets. However, these difficulties in synthesizing textures with non-local structures and extending dynamic or sound textures. In this article, ...

This paper addresses the problem of capturing the dynamics for exemplar-based recognition systems. Traditional HMM provides a probabilistic tool to capture system dynamics and in exemplar paradigm, HMM states are typically coupled with the exemplars. Alternatively, we propose a non-parametric HMM approach that uses a discrete HMM with arbitrary states (decoupled from exemplars) to capture the d...

We propose a novel image inpainting approach in which the exemplar and the sparse representation are combined together skillfully. In the process of image inpainting, often there will be such a situation: although the sum of squared differences (SSD) of exemplar patch is the smallest among all the candidate patches, there may be a noticeable visual discontinuity in the recovered image when usin...

Style transfer aims to apply the style of an exemplar model to a target one, while retaining the target’s structure. The main challenge in this process is to algorithmically distinguish style from structure, a high-level, potentially ill-posed cognitive task. Inspired by cognitive science research we recast style transfer in terms of shape analogies. In IQ testing, shape analogy queries present...