LensMaster: All-in-one Photorealistic Depth-of-field Rendering

Depth-of-field (DoF) editing remains challenging due to three limitations of existing methods: reliance on error-prone depth or segmentation priors, one-way rendering from all-in-focus inputs, and limited modeling of lens-dependent bokeh characteristics. We present LensMaster, an end-to-end framework that formulates DoF manipulation as a bidirectional optical-state transformation. Given a source image and its optical state, LensMaster continuously controls both focus distance and aperture to synthesize an arbitrary target state without explicit geometric priors. To support coherent editing across optical configurations, we introduce optical-state consistency with identity, cycle, and composition constraints. We further disentangle shared DoF transformation from lens-specific appearance through spatially varying lens-character modulation, enabling a single model to reproduce distinct real-lens Bokeh characteristics. To support cross-lens learning, we introduce FujiBokeh, a real-world multi-focus, multi-aperture dataset captured with a Fujifilm system. Experiments demonstrate that LensMaster achieves accurate continuous, bidirectional, and lens-aware DoF editing while preserving fine structures and realistic bokeh appearance.