UberNet: Training a universal convolutional neural network for Low-, Mid-, and high-level vision using diverse datasets and limited memory

Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017

Volumn 2017-January, Issue , 2017, Pages 5454-5463

  Kokkinos, Iasonas ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BUDGET CONTROL; C (PROGRAMMING LANGUAGE); CONVOLUTION; IMAGE SEGMENTATION; MEMORY ARCHITECTURE; NETWORK ARCHITECTURE; NEURAL NETWORKS; OBJECT DETECTION; SEMANTICS;

BOUNDARY DETECTION; COMPETITIVE PERFORMANCE; CONVOLUTIONAL NEURAL NETWORK; CONVOLUTIONAL NEURAL NETWORKS (CNN); DEEP ARCHITECTURES; HIGH-LEVEL VISIONS; SEMANTIC SEGMENTATION; UNIFIED ARCHITECTURE;

COMPUTER VISION;

EID: 85043458918     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2017.579     Document Type: Conference Paper

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