FlowChroma -- A Deep Recurrent Neural Network for Video Colorization
Thejan Wijesinghe Chamath Abeysinghe Chanuka Wijayakoon Lahiru Jayathilake Uthayasanker Thayasivam
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.