Automatic colorization of videos
نویسندگان
چکیده
Realistic colorization of videos has been of great interest to the artistic community, primarily for restoring historical color films and colorizing legacy videos. In this project, we experimented with several methods in order to automatically colorize videos on a frame-by-frame basis. We focused on rectifying two primary issues encountered with video colorizations : lack of color consistency between subsequent frames and desaturated colorization of individual frames. We used an LSTM to encode the sequential information of videos and thus maintain color consistency between successive frames. We used a class-rebalancing loss to reweight color predictions on the basis of their rarity. We evaluated out results using average per-pixel RMSE over all frames in a single video and also set up a colorization “Turing Test” to determine which models gave the most realistic colorization.
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