Deep Analog: Open-Set Film Emulation with Reference-Conditioned 3D LUTs

[2608.14702] Deep Analog: Open-Set Film Emulation with Reference-Conditioned 3D LUTs Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Computer Vision and Pattern Recognition arXiv:2608.14702 (cs) [Submitted on 10 Aug 2026] Title: Deep Analog: Open-Set Film Emulation with Reference-Conditioned 3D LUTs Authors: Yitong Mu View a PDF of the paper titled Deep Analog: Open-Set Film Emulation with Reference-Conditioned 3D LUTs, by Yitong Mu View PDF HTML (experimental) Abstract: Film emulation reproduces the look of an analog film stock on a new digital photograph. We target its open-set form -- matching any reference film frame from a single example -- with a 3D lookup table (LUT) predicted from that reference. Real-time image enhancement predicts per-image weights over a fixed bank of 3D LUTs and blends them. We show this is a gated mixture of experts and inherits its failure: trained end-to-end against reconstruction, the gate collapses onto a single expert, so a bank of K LUTs delivers the capacity of one. An entropy term, the enhancement-setting analogue of mixture-of-experts load balancing, restores utilization and recovers about 1 dB PSNR. The deeper constraint survives: a fixed LUT basis is closed-set, freezing the achievable looks at training time. We therefore discard the basis and predict a single 3D LUT as a residual from a reference image (StyleLUTNet), trained by self-supervision on procedurally generated color transforms. The conditional design removes the gate and generalizes open-set to unseen film stocks without paired data or retraining. Around this color backbone we build Deep Analog, a film-emulation pipeline that adds histogram-based tone matching and a physics-informed optical renderer -- multi-scale grain and per-channel halation driven by parameters an inverse network regresses from the reference. On 350 self-supervised pairs the color stage reaches 22.05 dB PSNR / 0.925 SSIM and the full pipeline 21.72 dB / 0.923; the color path runs in 5.2 ms at 1080p (192 FPS) and exports a portable .cube LUT for standard editing tools. A second degeneracy in conditional LUT training -- residual-scale collapse -- shares the root cause and yields a general principle: auxiliary regularization must stay subordinate to reconstruction. Comments: Master's thesis, Rochester Institute of Technology, 2026. 24 pages, 13 figures, 6 tables. Code and demo: this https URL Subjects: Computer Vision and Pattern Recognition (cs.CV) ; Graphics (cs.GR); Machine Learning (cs.LG); Multimedia (cs.MM) ACM classes: I.4.3; I.4.8; I.3.7; I.2.6 Cite as: arXiv:2608.14702 [cs.CV] (or arXiv:2608.14702v1 [cs.CV] for this version) https://doi.org/10.48550/arXiv.2608.14702 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Yitong Mu [ view email ] [v1] Mon, 10 Aug 2026 20:46:54 UTC (23,426 KB) Full-text links: Access Paper: View a PDF of the paper titled Deep Analog: Open-Set Film Emulation with Reference-Conditioned 3D LUTs, by Yitong Mu View PDF HTML (experimental) TeX Source view license Current browse context: cs.CV < prev | next > new | recent | 2026-08 Change to browse by: cs cs.GR cs.LG cs.MM References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... 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