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An extra-classical receptive field (ECRF) based mid-level model of visual processing which we refer to as the neuro-visually inspired model of figure-ground segregation (NFGS) is proposed in this work. It is inspired by the non-linear interaction of the classical receptive field (CRF) and its non-classical extended surround, comprising of the non-linear(More)
This paper addresses the problem of assigning object class labels to image pixels. Following recent holistic formulations, we cast scene labeling as inference of a conditional random field (CRF) grounded onto superpixels. The CRF inference is specified as quadratic program (QP) with mutual exclusion (mutex) constraints on class label assignments. The QP is(More)
This paper presents a novel deep architecture, called neural regression forest (NRF), for depth estimation from a single image. NRF combines random forests and convolutional neural networks (CNNs). Scanning windows extracted from the image represent samples which are passed down the trees of NRF for predicting their depth. At every tree node, the sample is(More)
Given a single RGB image our goal is to label every pixel with an affordance type. By affordance, we mean an object’s capability to readily support a certain human action, without requiring precursor actions. We focus on segmenting the following five affordance types in indoor scenes: ‘walkable’, ‘sittable’, ‘lyable’, ‘reachable’, and ‘movable’. Our(More)
The problem of local distinguishability of orthogonal quantum states has raised much interest in the arena of quantum information. Interestingly where any two pure orthogonal states can be distinguished locally [1], there exists more than two orthogonal states which can not be distinguished by local operations and classical communication (LOCC) [2, 3]. All(More)
This paper addresses the problem of weakly supervised semantic image segmentation. Our goal is to label every pixel in a new image, given only image-level object labels associated with training images. Our problem statement differs from common semantic segmentation, where pixelwise annotations are typically assumed available in training. We specify a novel(More)
A general multi-scale framework for multi-component, multi-phase equilibrium flash calculations, which uses information at the molecular and bulk fluid length scales, is described. The multi-scale Gibbs–Helmholtz constrained (GHC) EOS approach of Lucia (2010) is extended to include the use of (1) coarse grained NTP Monte Carlo simulations to gather pure(More)
Presence of duplicate documents in the World Wide Web adversely affects crawling, indexing and relevance, which are the core building blocks of web search. In this paper, we present a set of techniques to mine rules from URLs and utilize these learnt rules for de-duplication using just URL strings without fetching the content explicitly. Our technique is(More)