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cs.CV2024
Dense Scene Reconstruction from Light-Field Images Affected by Rolling Shutter
Hermes McGriff, Renato Martins, Nicolas Andreff +1
This paper presents a dense depth estimation approach from light-field (LF) images that is able to compensate for strong rolling shutter (RS) effects. Our method estimates RS compe…
cs.CV2024
Leveraging Semantic Cues from Foundation Vision Models for Enhanced Local Feature Correspondence
Felipe Cadar, Guilherme Potje, Renato Martins +2
Visual correspondence is a crucial step in key computer vision tasks, including camera localization, image registration, and structure from motion. The most effective techniques fo…