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WP.L2: Single-Image Super-Resolution

Session Type: Lecture

Time: Wednesday, September 28, 14:00 - 17:10

Location: Room 106 C

Session Chair: Aggelos Katsaggelos, Northwestern University

Presented 14:00 - 14:20

WP.L2.1: TURNING A DENOISER INTO A SUPER-RESOLVER USING PLUG AND PLAY PRIORS

Alon Brifman; Technion

Yaniv Romano; Technion

Michael Elad; Technion

Presented 14:20 - 14:40

WP.L2.2: STRUCTURE PRESERVING SINGLE IMAGE SUPER-RESOLUTION

Fan Yang; Peking University

Don Xie; Peking University

Huizhu Jia; Peking University

Rui Chen; Peking University

Guoqing Xiang; Peking University

Wen Gao; Peking University

Presented 14:40 - 15:00

WP.L2.3: FINDING THE RIGHT EXEMPLARS FOR RECONSTRUCTING SINGLE IMAGE SUPER-RESOLUTION

Jiahuan Zhou; Northwestern University

Ying Wu; Northwestern University

Presented 15:00 - 15:20

WP.L2.4: BOOSTING PERFORMANCE AND SPEED OF SINGLE-IMAGE SUPER-RESOLUTION BASED ON PARTITIONED LINEAR REGRESSION

Anustup Choudhury; Dolby Laboratories Inc.

Peter van Beek; Sharp Laboratories of America

Break

Presented 15:50 - 16:10

WP.L2.5: LOW-RANK SPARSE REPRESENTATION FOR SINGLE IMAGE SUPER-RESOLUTION VIA SELF-SIMILARITY LEARNING

Jiahe Shi; Xi'an Jiaotong University

Chun Qi; Xi'an Jiaotong University

Presented 16:10 - 16:30

WP.L2.6: IMAGE SUPER-RESOLUTION VIA DUAL-MANIFOLD CLUSTERING AND SUBSPACE SIMILARITY

Mohammed Al-Qizwini; Michigan State University

Chinh Dang; Michigan State University

Mohammad Aghagolzadeh; Michigan State University

Hayder Radha; Michigan State University

Presented 16:30 - 16:50

WP.L2.7: FAST IMAGE SUPER-RESOLUTION VIA MULTIPLE DIRECTIONAL TRANSFORMS

Zhiyu Chen; Niigata University

Shogo Muramatsu; Niigata University

Yoshito Abe; Industrial Research Institute of Niigata Prefecture

Presented 16:50 - 17:10

WP.L2.8: A HYBRID WAVELET CONVOLUTION NETWORK WITH SPARSE-CODING FOR IMAGE SUPER-RESOLUTION

Xing Gao; Shanghai Jiao Tong University

Hongkai Xiong; Shanghai Jiao Tong University