CVJun 4, 2024

Optimised ProPainter for Video Diminished Reality Inpainting

arXiv:2406.02287v13 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the problem of clearer operative field views for medical professionals, but it is incremental as it refines an existing method for a specific domain.

The paper tackled video inpainting for medical imaging in oral and maxillofacial surgery by optimizing the ProPainter method, resulting in a technique that produces temporally coherent and detail-rich reconstructions without requiring training.

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.

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