A Computational Investigation into the Human Representation and Processing of Visual Information

By Catherine Brandei, Victor Royer, D. Marr. 2011

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

BAM: Bottleneck Attention Module (2018, neutral): “More visualizations and analysis are included in the supplementary material due to space constraints.”
Performance-optimized hierarchical models predict neural responses in higher visual cortex (2014, background): “Our results show that behaviorally driven computational approaches have an important role in understanding the details of visual processing (37) and suggest that the overall approach may be applicable to other cortical areas and task domains.”
Piecewise Flat Embedding for Image Segmentation (2018, background): “It supports high-level visual inference and perception [1] such as figure/ground analysis and object discovery.”
Hierarchical Modular Optimization of Convolutional Networks Achieves Representations Similar to Macaque IT and Human Ventral Stream (2013, result): “Our results show that behaviorally-driven computational approaches have an important role in understanding the details of cortical processing[24].”
How cognitive modeling can benefit from hierarchical Bayesian models. (2011, background): “Most existing work has focused on providing 'rational' accounts of psychological phenomena, pitched at the computational level within the three-level hierarchy described by Marr (1982).”