Lazebnik, Svetlana - Department of Computer Science, University of North Carolina at Chapel Hill

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Lazebnik, Svetlana - Department of Computer Science, University of North Carolina at Chapel Hill

An Empirical Bayes Approach to Contextual Region Classification Svetlana Lazebnik
July 28, 2004 18:40 WSPC/Trim Size: 9.75in x 6.5in for Review Volume schmid CHAPTER 1.5
Fast Robust Reconstruction of Large Scale Environments
Building Rome on a Cloudless Day Jan-Michael Frahm1
ANALYSIS OF HUMAN ATTRACTIVENESS USING MANIFOLD KERNEL REGRESSION B. C. Davis and S. Lazebnik
Comparing Data-Dependent and Data-Independent Embeddings for Classification and Ranking of Internet Images
Noname manuscript No. (will be inserted by the editor)
SuperParsing: Scalable Nonparametric Image Parsing with Superpixels
Supervised Learning of Quantizer Codebooks by Information Loss Minimization
Computing Iconic Summaries of General Visual Concepts Rahul Raguram Svetlana Lazebnik
Learning Nearest-Neighbor Quantizers from Labeled Data by Information Loss Minimization
LOCAL, SEMI-LOCAL AND GLOBAL MODELS FOR TEXTURE, OBJECT AND SCENE RECOGNITION
3D Object Modeling and Recognition Using Local Affine-Invariant Image Descriptors and Multi-View Spatial Constraints
A Maximum Entropy Framework for Part-Based Texture and Object Recognition Svetlana Lazebnik
A Sparse Texture Representation Using Local Affine Regions
Toward True 3D Object Recognition Jean Ponce1
A Sparse Texture Representation Using Affine-Invariant Regions Svetlana Lazebnik Cordelia Schmid Jean Ponce
3D Object Modeling and Recognition Using Affine-Invariant Patches and Multi-View Spatial Constraints
3D Photography from Photographs and Video Clips Jean Ponce(1)
PROJECTIVE VISUAL HULLS Beckman CVR Technical Report 200201
Visibility-Based Pursuit-Evasion in Three-Dimensional Environments
On Computing Exact Visual Hulls of Solids Bounded by Smooth Surfaces Svetlana Lazebnik Edmond Boyer Jean Ponce
Iterative Quantization: A Procrustean Approach to Learning Binary Codes Yunchao Gong and Svetlana Lazebnik
SuperParsing: Scalable Nonparametric Image Parsing with Superpixels Joseph Tighe and Svetlana Lazebnik Dept. of Computer Science, University of North Carolina at Chapel Hill http://www.cs.unc.edu/SuperParsing
The Local Projective Shape of Smooth Surfaces and their Outlines Svetlana Lazebnik Jean Ponce
Spatial Pyramid Matching Svetlana Lazebnik (lazebnik@cs.unc.edu)
Fast Robust Large-scale Mapping from Video and Internet Photo Collections
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
Semi-Local Affine Parts for Object Recognition Svetlana Lazebnik1 Cordelia Schmid2 Jean Ponce1
The Local Projective Shape of Smooth Surfaces and Their Outlines
Estimation of Intrinsic Dimensionality Using High-Rate Vector Quantization
Scene Recognition and Weakly Supervised Object Localization with Deformable Part-Based Models
Understanding Scenes on Many Levels Joseph Tighe and Svetlana Lazebnik
IEEE TRANSACTION ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 1 Iterative Quantization