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Computer Vision – ECCV 2014
Deep Features for Text Spotting
other
Author(s):
Max Jaderberg
,
Andrea Vedaldi
,
Andrew Zisserman
Publication date
(Print):
2014
Publisher:
Springer International Publishing
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Radiology and Natural Language Processing
Author and book information
Book Chapter
Publication date (Print):
2014
Pages
: 512-528
DOI:
10.1007/978-3-319-10593-2_34
SO-VID:
3f906b61-cdd6-4fc3-b812-ef67e9477443
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Book chapters
pp. 215
Modeling Video Dynamics with Deep Dynencoder
pp. 828
On Sampling Focal Length Values to Solve the Absolute Pose Problem
pp. 90
Consistent Matting for Light Field Images
pp. 105
Consensus of Regression for Occlusion-Robust Facial Feature Localization
pp. 184
Learning a Deep Convolutional Network for Image Super-Resolution
pp. 263
View-Consistent 3D Scene Flow Estimation over Multiple Frames
pp. 341
Bilateral Functions for Global Motion Modeling
pp. 372
Single-Image Super-Resolution: A Benchmark
pp. 387
Well Begun Is Half Done: Generating High-Quality Seeds for Automatic Image Dataset Construction from Web
pp. 401
Zero-Shot Learning via Visual Abstraction
pp. 450
Parameterizing Object Detectors in the Continuous Pose Space
pp. 466
Jointly Optimizing 3D Model Fitting and Fine-Grained Classification
pp. 497
Robust Scene Text Detection with Convolution Neural Network Induced MSER Trees
pp. 512
Deep Features for Text Spotting
pp. 529
Improving Image-Sentence Embeddings Using Large Weakly Annotated Photo Collections
pp. 562
Selecting Influential Examples: Active Learning with Expected Model Output Changes
pp. 593
Continuous Conditional Neural Fields for Structured Regression
pp. 624
Support Vector Guided Dictionary Learning
pp. 656
Supervoxel-Consistent Foreground Propagation in Video
pp. 688
Person Re-identification by Video Ranking
pp. 720
Face Detection without Bells and Whistles
pp. 796
Total Moving Face Reconstruction
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