Image Super-Resolution via Dual-State Recurrent Networks

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2018, Pages 1654-1663

  Han, Wei ^a   Chang, Shiyu ^b   Liu, Ding ^a   Yu, Mo ^b   Witbrock, Michael ^b   Huang, Thomas S ^a  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b IBM RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; OPTICAL RESOLVING POWER; RECURRENT NEURAL NETWORKS;

BENCHMARK DATASETS; IMAGE SUPER RESOLUTIONS; MEMORY CONSUMPTION; PREDICTIVE ACCURACY; QUALITATIVE EVALUATIONS; RECURRENT NETWORKS; RECURRENT NEURAL NETWORK (RNN); STATE-OF-THE-ART ALGORITHMS;

DEEP NEURAL NETWORKS;

EID: 85062859914     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2018.00178     Document Type: Conference Paper

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