In this episode we discuss JAWS: Just A Wild Shot for Cinematic Transfer in Neural Radiance Fields
by Xi Wang, Robin Courant, Jinglei Shi, Eric Marchand, Marc Christie. The paper introduces JAWS, an optimization-driven approach to transfer visual cinematic features from a reference video clip to a newly generated clip, using implicit neural representations. The method computes cinematic features in an INR and optimizes extrinsic and intrinsic camera parameters and timing to replicate the reference clip. The approach leverages the differentiability of neural representations to backpropagate cinematic losses through a NeRF network and includes enhancements like guidance maps for quality improvement. Results demonstrate successful replication of well-known cinematic sequences.
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