End-to-End Online Video Stitching and Stabilization Method Based on Unsupervised Deep Learning
The limited field of view, cumulative inter-frame jitter, and dynamic parallax interference in handheld video stitching often lead to misalignment and distortion. In this paper, we propose an end-to-end, unsupervised deep-learning framework that jointly performs real-time video stabilization and sti...
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| Autori principali: | , , , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI AG
2025-05-01
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| Serie: | Applied Sciences |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/2076-3417/15/11/5987 |
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