  This paper summarizes the cinematic demixing (CDX) track of the Sound
Demixing Challenge 2023 (SDX'23). We provide a comprehensive summary of the
challenge setup, detailing the structure of the competition and the datasets
used. Especially, we detail CDXDB23, a new hidden dataset constructed from real
movies that was used to rank the submissions. The paper also offers insights
into the most successful approaches employed by participants. Compared to the
cocktail-fork baseline, the best-performing system trained exclusively on the
simulated Divide and Remaster (DnR) dataset achieved an improvement of 1.8 dB
in SDR, whereas the top-performing system on the open leaderboard, where any
data could be used for training, saw a significant improvement of 5.7 dB. A
significant source of this improvement was making the simulated data better
match real cinematic audio, which we further investigate in detail.
