Optimised ProPainter for Video Diminished Reality Inpainting
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866916273860902912 |
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| author | Li, Pengze Liu, Lihao Schönlieb, Carola-Bibiane Aviles-Rivero, Angelica I |
| author_facet | Li, Pengze Liu, Lihao Schönlieb, Carola-Bibiane Aviles-Rivero, Angelica I |
| contents | In this paper, part of the DREAMING Challenge - Diminished Reality for Emerging Applications in Medicine through Inpainting, we introduce a refined video inpainting technique optimised from the ProPainter method to meet the specialised demands of medical imaging, specifically in the context of oral and maxillofacial surgery. Our enhanced algorithm employs the zero-shot ProPainter, featuring optimized parameters and pre-processing, to adeptly manage the complex task of inpainting surgical video sequences, without requiring any training process. It aims to produce temporally coherent and detail-rich reconstructions of occluded regions, facilitating clearer views of operative fields. The efficacy of our approach is evaluated using comprehensive metrics, positioning it as a significant advancement in the application of diminished reality for medical purposes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_02287 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Optimised ProPainter for Video Diminished Reality Inpainting Li, Pengze Liu, Lihao Schönlieb, Carola-Bibiane Aviles-Rivero, Angelica I Computer Vision and Pattern Recognition In this paper, part of the DREAMING Challenge - Diminished Reality for Emerging Applications in Medicine through Inpainting, we introduce a refined video inpainting technique optimised from the ProPainter method to meet the specialised demands of medical imaging, specifically in the context of oral and maxillofacial surgery. Our enhanced algorithm employs the zero-shot ProPainter, featuring optimized parameters and pre-processing, to adeptly manage the complex task of inpainting surgical video sequences, without requiring any training process. It aims to produce temporally coherent and detail-rich reconstructions of occluded regions, facilitating clearer views of operative fields. The efficacy of our approach is evaluated using comprehensive metrics, positioning it as a significant advancement in the application of diminished reality for medical purposes. |
| title | Optimised ProPainter for Video Diminished Reality Inpainting |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2406.02287 |