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Found 7 papers, 3 papers with code
A Too-Good-to-be-True Prior to Reduce Shortcut Reliance
Furthermore, an LCN's predictions can be used in a two-stage approach to encourage a high-capacity network (HCN) to rely on deeper invariant features that should generalize broadly.
Enriching ImageNet with Human Similarity Judgments and Psychological Embeddings
The Human Similarity Judgments extension to ImageNet (ImageNet-HSJ) is composed of human similarity judgments that supplement the ILSVRC validation set.
Transforming Neural Network Visual Representations to Predict Human Judgments of Similarity
Deep-learning vision models have shown intriguing similarities and differences with respect to human vision.
The perceptual boost of visual attention is task-dependent in naturalistic settings
Is the resulting perceptual boost task-dependent in naturalistic settings?
The Costs and Benefits of Goal-Directed Attention in Deep Convolutional Neural Networks
Motivated by selective attention in categorisation models, we developed a goal-directed attention mechanism that can process naturalistic (photographic) stimuli.
Learning as the Unsupervised Alignment of Conceptual Systems
Concept induction requires the extraction and naming of concepts from noisy perceptual experience.
Learning to Generate Images with Perceptual Similarity Metrics
We propose instead to use a loss function that is better calibrated to human perceptual judgments of image quality: the multiscale structural-similarity score (MS-SSIM).
