The following publications are possibly variants of this publication:
- Multi-scale attention network for image super-resolutionLi Wang, Jie Shen 0004, E. Tang, Shengnan Zheng, Lizhong Xu. jvcir, 80:103300, 2021. [doi]
- Guided Cascaded Super-Resolution Network for Face ImageLin Cao, Jiape Liu, Kangning Du, Yanan Guo, Tao Wang 0035. access, 8:173387-173400, 2020. [doi]
- Augmented global attention network for image super-resolutionXiaobiao Du, Sai Biao Jiang, Jie Liu. iet-ipr, 16(2):567-575, 2022. [doi]
- SCTANet: A Spatial Attention-Guided CNN-Transformer Aggregation Network for Deep Face Image Super-ResolutionQiqi Bao, Yunmeng Liu, Bowen Gang, Wenming Yang, Qingmin Liao. tmm, 25:8554-8565, 2023. [doi]
- Image super-resolution with multi-scale fractal residual attention networkXiaogang Song, Wanbo Liu, Li Liang, Weiwei Shi 0003, Guo Xie, Xiaofeng Lu, Xinhong Hei 0001. cg, 113:21-31, June 2023. [doi]
- Multi-scale convolutional attention network for lightweight image super-resolutionFeng Xie, Pei Lu, Xiaoyong Liu. jvcir, 95:103889, September 2023. [doi]
- A Lightweight Multi-Scale Based Attention Network for Image Super-ResolutionYanjie Yang, Jun Luo, Huayan Pu, Mingliang Zhou, Xuekai Wei, Taiping Zhang, Zhaowei Shang. iecon 2023: 1-6 [doi]