Details

Autor(en) / Beteiligte

• Isobe, Takashi
• Li, Songjiang
• Jia, Xu
• Yuan, Shanxin
• Slabaugh, Gregory
• Xu, Chunjing
• Li, Ya-Li
• Wang, Shengjin
• Tian, Qi

Titel

Video Super-Resolution With Temporal Group Attention

Ist Teil von

• 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, p.8005-8014

Ort / Verlag

IEEE

Erscheinungsjahr

2020

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• Video super-resolution, which aims at producing a high-resolution video from its corresponding low-resolution version, has recently drawn increasing attention. In this work, we propose a novel method that can effectively incorporate temporal information in a hierarchical way. The input sequence is divided into several groups, with each one corresponding to a kind of frame rate. These groups provide complementary information to recover missing details in the reference frame, which is further integrated with an attention module and a deep intra-group fusion module. In addition, a fast spatial alignment is proposed to handle videos with large motion. Extensive results demonstrate the capability of the proposed model in handling videos with various motion. It achieves favorable performance against state-of-the-art methods on several benchmark datasets.