  Film, a classic image style, is culturally significant to the whole
photographic industry since it marks the birth of photography. However, film
photography is time-consuming and expensive, necessitating a more efficient
method for collecting film-style photographs. Numerous datasets that have
emerged in the field of image enhancement so far are not film-specific. In
order to facilitate film-based image stylization research, we construct
FilmSet, a large-scale and high-quality film style dataset. Our dataset
includes three different film types and more than 5000 in-the-wild high
resolution images. Inspired by the features of FilmSet images, we propose a
novel framework called FilmNet based on Laplacian Pyramid for stylizing images
across frequency bands and achieving film style outcomes. Experiments reveal
that the performance of our model is superior than state-of-the-art techniques.
The link of code and data is \url{https://github.com/CXH-Research/FilmNet}.
