8 papers with code • 0 benchmarks • 0 datasets
These leaderboards are used to track progress in Foveation
The primary model has a foveated-textural input stage, which we compare to a model with foveated-blurred input and a model with spatially-uniform blurred input (both matched for perceptual compression), and a final reference model with minimal input-based compression.
Deep Co-attention based Comparators For Relative Representation Learning in Person Re-identification
Recent effective methods are developed in a pair-wise similarity learning system to detect a fixed set of features from distinct regions which are mapped to their vector embeddings for the distance measuring.
We demonstrate on three publicly available high-resolution image datasets that the foveation module consistently improves segmentation performance over the cases trained with patches of fixed FoV/resolution trade-off.
Finally, the model of target detectability is used in a Bayesian ideal observer model of visual search, and compared to human search performance.
The spatially-varying field of the human visual system has recently received a resurgence of interest with the development of virtual reality (VR) and neural networks.
Compared to human vision, computer vision based on convolutional neural networks (CNN) are more vulnerable to adversarial noises.