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README.md

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+# APISR Model Card
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+<div align="center">
+
+[**Paper (ArXiv)**](https://arxiv.org/pdf/2403.01598.pdf) **|** [**Code**](https://github.com/Kiteretsu77/APISR) **|** [🤗 **Gradio demo**](https://huggingface.co/spaces/HikariDawn/APISR) 
+
+</div>
+
+## Introduction
+While real-world anime super-resolution (SR) has gained increasing attention in the SR community, existing methods still adopt techniques from the photorealistic
+domain. In this paper, we analyze the anime production workflow and rethink how to use characteristics of it for the sake of the real-world anime SR. First, we argue that
+video networks and datasets are not necessary for anime
+SR due to the repetition use of hand-drawing frames. Instead, we propose an anime image collection pipeline by
+choosing the least compressed and the most informative
+frames from the video sources. Based on this pipeline,
+we introduce the Anime Production-oriented Image (API)
+dataset. In addition, we identify two anime-specific challenges of distorted and faint hand-drawn lines and unwanted color artifacts. We address the first issue by introducing a prediction-oriented compression module in the
+image degradation model and a pseudo-ground truth preparation with enhanced hand-drawn lines. In addition, we introduce the balanced twin perceptual loss combining both
+anime and photorealistic high-level features to mitigate unwanted color artifacts and increase visual clarity. We evaluate our method through extensive experiments on the public
+benchmark, showing our method outperforms state-of-the-art anime dataset-trained approaches.
+
+&ensp;
+
+<div align="center">
+    <img src="https://raw.githubusercontent.com/Kiteretsu77/APISR/blob/main/__assets__/workflow.png", width="100%", height="100%", style="float: left">
+</div>
+