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arXiv · 2305.13704

FlowChroma -- A Deep Recurrent Neural Network for Video Colorization

Thejan Wijesinghe·Chamath Abeysinghe·Chanuka Wijayakoon·Lahiru Jayathilake·Uthayasanker Thayasivam
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Abstract

We develop an automated video colorization framework that minimizes the flickering of colors across frames. If we apply image colorization techniques to successive frames of a video, they treat each frame as a separate colorization task. Thus, they do not necessarily maintain the colors of a scene consistently across subsequent frames. The proposed solution includes a novel deep recurrent encoder-decoder architecture which is capable of maintaining temporal and contextual coherence between consecutive frames of a video. We use a high-level semantic feature extractor to automatically identify the context of a scenario including objects, with a custom fusion layer that combines the spatial and temporal features of a frame sequence. We demonstrate experimental results, qualitatively showing that recurrent neural networks can be successfully used to improve color consistency in video colorization.

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Thejan Wijesinghe, Chamath Abeysinghe, Chanuka Wijayakoon, Lahiru Jayathilake, Uthayasanker Thayasivam. 2023-05-23. FlowChroma -- A Deep Recurrent Neural Network for Video Colorization. https://doi.org/10.1007/978-3-030-50347-5_2

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