1 On what it means to see , and what we can do about it

By Michael Tarr. 2008

Subfields: Computer Vision and Pattern Recognition

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Citations in the corpus

Framing Image Description as a Ranking Task: Data, Models and Evaluation Metrics (2013, background): “…K Histo (x i , x j ) = 1 3 F ∈{C,S,T} K Histo F (x i , x j ) p (6) Hodosh, Young & Hockenmaier 3.3.2 The Pyramid Kernel K Py The spatial pyramid kernel (Lazebnik et al., 2009) is a generalization of the histogram kernel that captures similarities not just at a global, but also at a local level.”
Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream (2014, background): “For additional information about this publication click this link. http://hdl.handle.net/2066/142442 Please be advised that this information was generated on 2019-12-21 and may be subject to change.”
Discriminatively Activated Sparselets (2013, background): “Our work is related to three strands of active research: (1) part sharing with compositional models (Torralba et al., 2007; Fidler et al., 2009; Zhu et al., 2010; Ott & Everingham, 2011; Girshick et al., 2011), (2) sparse coding and dictionary learning (Kreutz-Delgado et al., 2003; Mairal et al.,…”
STNet: Selective Tuning of Convolutional Networks for Object Localization (2017, background): “In recent years, while the learning approaches have been matured, various models and algorithms have been developed to present a richer visual representation for various visual tasks such as object classification and detection, semantic segmentation, action recognition, and scene understanding [1, 7”
50 Years of object recognition: Directions forward (2013, background): “Edelman argues that the use of intermediate representations instead of full geometric reconstruction, is a necessary condition for building a versatile artificial vision system.”
Deep Hierarchies in the Primate Visual Cortex: What Can We Learn for Computer Vision? (2013, background): “Interactions between the disciplines of " biological vision " and " computer vision " have varied in intensity throughout the course of computer vision history and have in some way reflected the changing research focuses of the machine vision community [32].”
Prototype-Incorporated Emotional Neural Network (2018, background): “However, for us to breakthrough in machine intelligence and vision, we must first understand the basis of learning and visual processing in humans [13], [14].”