Core Concepts
The authors propose APISR, leveraging anime production workflow for real-world super-resolution, introducing a novel dataset and addressing specific challenges in anime SR.
Abstract
The paper introduces APISR, focusing on real-world anime super-resolution by analyzing the anime production process. They propose an Anime Production-oriented Image (API) dataset and address challenges like distorted hand-drawn lines and unwanted color artifacts. The method outperforms existing approaches in extensive experiments.
The authors analyze the unique aspects of anime production to enhance real-world super-resolution. They introduce a novel dataset collection pipeline focusing on keyframes and image complexity assessment. Additionally, they address challenges like faint hand-drawn lines and unwanted color artifacts with innovative solutions.
By leveraging insights from the anime production process, the authors propose a comprehensive approach to improve real-world anime super-resolution. They introduce a new dataset, tackle specific challenges in restoration, and achieve superior results compared to state-of-the-art methods.
The study delves into the intricacies of anime production to enhance real-world super-resolution techniques. Introducing a specialized dataset and addressing unique challenges in restoration lead to significant improvements over existing methods.
Stats
"Our method outperforms state-of-the-art approaches by a large margin."
"We evaluate our method through extensive experiments on the public benchmark."
"Our model has the smallest network size but has SOTA performance in all metrics."