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39 Result(s)
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Pushmeet Kohli
Computer Science
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Reference Work Entry In depth
Semantic Image Segmentation: Traditional Approach
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Living Reference Work Entry In depth
Semantic Image Segmentation: Traditional Approach
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Chapter and Conference Paper
Learning Shape Analysis
We present a data-driven verification framework to automatically prove memory safety of heap-manipulating programs. Our core contribution is a novel statistical machine learning technique that maps observed pr...
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Chapter and Conference Paper
Deep Disentangled Representations for Volumetric Reconstruction
We introduce a convolutional neural network for inferring a compact disentangled graphical description of objects from 2D images that can be used for volumetric reconstruction. The network comprises an encoder...
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Chapter and Conference Paper
Overcoming Occlusion with Inverse Graphics
Scene understanding tasks such as the prediction of object pose, shape, appearance and illumination are hampered by the occlusions often found in images. We propose a vision-as-inverse-graphics approach to han...
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Chapter and Conference Paper
Efficient Continuous Relaxations for Dense CRF
Dense conditional random fields (CRF) with Gaussian pairwise potentials have emerged as a popular framework for several computer vision applications such as stereo correspondence and semantic segmentation. By ...
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Article
Fast and accurate scene text understanding with image binarization and off-the-shelf OCR
While modern off-the-shelf OCR engines show particularly high accuracy on scanned text, text detection and recognition in natural images still remain a challenging problem. Here, we demonstrate that OCR engine...
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Chapter and Conference Paper
Faster and More Dynamic Maximum Flow by Incremental Breadth-First Search
We introduce the Excesses Incremental Breadth-First Search (Excesses IBFS) algorithm for maximum flow problems. We show that Excesses IBFS has the best overall practical performance on real-world instances, while...
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Chapter and Conference Paper
Multi-utility Learning: Structured-Output Learning with Multiple Annotation-Specific Loss Functions
Structured-output learning is a challenging problem; particularly so because of the difficulty in obtaining large datasets of fully labelled instances for training. In this paper we try to overcome this diffic...
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Article
Manifestations of user personality in website choice and behaviour on online social networks
Individual differences in personality affect users’ online activities as much as they do in the offline world. This work, based on a sample of over a third of a million users, examines how users’ behaviour in ...
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Book
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Reference Work Entry In depth
Semantic Image Segmentation
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Chapter and Conference Paper
Perceptually Inspired Layout-Aware Losses for Image Segmentation
Interactive image segmentation is an important computer vision problem that has numerous real world applications. Models for image segmentation are generally trained to minimize the Hamming error in pixel labe...
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Chapter and Conference Paper
A Contour Completion Model for Augmenting Surface Reconstructions
The availability of commodity depth sensors such as Kinect has enabled development of methods which can densely reconstruct arbitrary scenes. While the results of these methods are accurate and visually appeal...
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Chapter and Conference Paper
Non-parametric Higher-Order Random Fields for Image Segmentation
Models defined using higher-order potentials are becoming increasingly popular in computer vision. However, the exact representation of a general higher-order potential defined over many variables is computati...
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Article
Inference Methods for CRFs with Co-occurrence Statistics
The Markov and Conditional random fields (CRFs) used in computer vision typically model only local interactions between variables, as this is generally thought to be the only case that is computationally tract...
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Chapter
Key Developments in Human Pose Estimation for Kinect
The last few years have seen a surge in the development of natural user interfaces. These interfaces do not require devices such as keyboards and mice that have been the dominant modes of interaction over the ...
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Article
User-Centric Learning and Evaluation of Interactive Segmentation Systems
Many successful applications of computer vision to image or video manipulation are interactive by nature. However, parameters of such systems are often trained neglecting the user. Traditionally, interactive s...
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Article
Geometric Image Parsing in Man-Made Environments
We present a new optimization based parsing framework for the geometric analysis of a single image coming from a man-made environment. This framework models the scene as a composition of geometric primitives s...
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Chapter and Conference Paper
Curvature Prior for MRF-Based Segmentation and Shape Inpainting
Most image labeling problems such as segmentation and image reconstruction are fundamentally ill-posed and suffer from ambiguities and noise. Higher-order image priors encode high-level structural dependencies...
