LensStyle: Learning the Optical Aesthetics for Controllable Stylized Lens Effect Rendering
作者: Yachuan Huang, Liwen Xiao, Liao Shen, QiWen Wang, Huiqiang Sun, Zhiyu Pan, Zhiguo Cao
摘要
The visual aesthetics of photographs are deeply influencedby lens characteristics such as aperture shape, optical vignetting and op-tical diffraction, which together define a camera’s unique optical style.Existing lens effect rendering methods primarily focus on accurately sim-ulating the blur transition from small to large apertures but overlook thestylistic aspects of lens effects. As a result, they fail to produce diversebokeh effects under large apertures or capture distinctive photographicphenomena such as starbursts that emerge under small apertures. In thiswork, we introduce LensStyle, a unified framework for controllable styl-ized lens effect rendering that explicitly models lens aesthetics throughjoint continuous–discrete control. Our model incorporates a Dual-PathController that disentangles continuous optical parameter modulation(e.g., focus distance and blur strength) from discrete lens-style condi-tioning (e.g., circular, polygonal, donut, cat-eye, and starburst effects),enabling fine-grained, interpretable, and physically grounded lens manip-ulation within a single unified framework. To support model training, wecurate a comprehensive MultiLens dataset containing multi-lens imagepairs synthesized under real optical constraints. Extensive experimentsdemonstrate that LensStyle achieves superior realism, controllability, andaesthetic quality compared with existing lens effect rendering approachesand diffusion-based image editing models, advancing computational pho-tography toward multiple-lens-style simulation.