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arXiv · 2408.11411

SelfDRSC++: Self-Supervised Dual Reversed Rolling Shutter Correction via Video Interpolation

Wei Shang·Dongwei Ren·Wanying Zhang·Qilong Wang·Pengfei Zhu·Wangmeng Zuo
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Abstract

Modern consumer cameras often use rolling shutter, capturing scenes row-by-row and causing distortion in dynamic scenes. Existing correction methods rely on supervised learning with high-frame-rate global shutter images as ground truth. We propose SelfDRSC++, a self-supervised framework for RS distortion correction {from simultaneously captured top-to-bottom and bottom-to-top RS images}. A lightweight network with a bidirectional correlation matching block jointly optimizes optical flows and corrected RS features, improving performance with fewer parameters. A self-supervised strategy enforces {a physically constrained RS--GS--RS cycle} between input and reconstructed dual reversed RS images. RS reconstruction is formulated as a specialized video frame interpolation task, enabling feasible one-stage training. Extensive experiments on synthetic and real-world data show that SelfDRSC++ achieves competitive quantitative performance, improves perceptual quality, and produces high-frame-rate GS sequences with better temporal consistency.

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Wei Shang, Dongwei Ren, Wanying Zhang, Qilong Wang, Pengfei Zhu, Wangmeng Zuo. 2024-08-21. SelfDRSC++: Self-Supervised Dual Reversed Rolling Shutter Correction via Video Interpolation. https://arxiv.org/abs/2408.11411

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