تقرير
Bridging the Gap: Fine-to-Coarse Sketch Interpolation Network for High-Quality Animation Sketch Inbetweening
| العنوان: | Bridging the Gap: Fine-to-Coarse Sketch Interpolation Network for High-Quality Animation Sketch Inbetweening |
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| المؤلفون: | Shen, Jiaming, Hu, Kun, Bao, Wei, Chen, Chang Wen, Wang, Zhiyong |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Multimedia |
| الوصف: | The 2D animation workflow is typically initiated with the creation of keyframes using sketch-based drawing. Subsequent inbetweens (i.e., intermediate sketch frames) are crafted through manual interpolation for smooth animations, which is a labor-intensive process. Thus, the prospect of automatic animation sketch interpolation has become highly appealing. However, existing video interpolation methods are generally hindered by two key issues for sketch inbetweening: 1) limited texture and colour details in sketches, and 2) exaggerated alterations between two sketch keyframes. To overcome these issues, we propose a novel deep learning method, namely Fine-to-Coarse Sketch Interpolation Network (FC-SIN). This approach incorporates multi-level guidance that formulates region-level correspondence, sketch-level correspondence and pixel-level dynamics. A multi-stream U-Transformer is then devised to characterize sketch inbewteening patterns using these multi-level guides through the integration of both self-attention and cross-attention mechanisms. Additionally, to facilitate future research on animation sketch inbetweening, we constructed a large-scale dataset - STD-12K, comprising 30 sketch animation series in diverse artistic styles. Comprehensive experiments on this dataset convincingly show that our proposed FC-SIN surpasses the state-of-the-art interpolation methods. Our code and dataset will be publicly available. Comment: 7pages,6figures |
| نوع الوثيقة: | Working Paper |
| الوصول الحر: | http://arxiv.org/abs/2308.13273Test |
| رقم الانضمام: | edsarx.2308.13273 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |