ProMist-5K: A Comprehensive Dataset for Digital Emulation of Cinematic Pro-Mist Filter Effects
Yingtie Lei, Zimeng Li, Chi-Man Pun, Wangyu Wu, Junke Yang, Xuhang Chen

TL;DR
ProMist-5K is a high-resolution dataset designed to digitally emulate cinematic pro-mist filter effects, capturing realistic glow and diffusion for improved style transfer in film-inspired imagery.
Contribution
It introduces a physically inspired, scene-referred dataset with 20,000 image pairs focused on realistic diffusion effects for cinematic style emulation.
Findings
Dataset effectively supports various image translation models.
Captures both subtle and strong cinematic diffusion effects.
Enhances digital reproduction of traditional lens aesthetics.
Abstract
Pro-Mist filters are widely used in cinematography for their ability to create soft halation, lower contrast, and produce a distinctive, atmospheric style. These effects are difficult to reproduce digitally due to the complex behavior of light diffusion. We present ProMist-5K, a dataset designed to support cinematic style emulation. It is built using a physically inspired pipeline in a scene-referred linear space and includes 20,000 high-resolution image pairs across four configurations, covering two filter densities (1/2 and 1/8) and two focal lengths (20mm and 50mm). Unlike general style datasets, ProMist-5K focuses on realistic glow and highlight diffusion effects. Multiple blur layers and carefully tuned weighting are used to model the varying intensity and spread of optical diffusion. The dataset provides a consistent and controllable target domain that supports various image…
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Taxonomy
TopicsImage Enhancement Techniques · Generative Adversarial Networks and Image Synthesis · Computer Graphics and Visualization Techniques
