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On the other hand, we propose EFENet by exploring the diversity of multiple encoded features and ensemble strategies of features (e.g., group-channel uniformly weighted average ensemble and self-gate weighted ensemble). Diversity is represented by encoded features with less parameters, and a simple mean squared error loss can achieve the superior performance. Experimental results demonstrate the superiority over the state-of-the-arts in terms of accuracy and speed. Codes and models are available at https//github.com/wdzhao123/DENets.Super Resolution (SR) im