Citation and History ==================== If you use DeepLens in your research, please cite the relevant papers. Primary Citation ---------------- **Curriculum Learning for Ab Initio Deep Learned Refractive Optics** .. code-block:: bibtex @article{yang2024curriculum, title={Curriculum learning for ab initio deep learned refractive optics}, author={Yang, Xinge and Fu, Qiang and Heidrich, Wolfgang}, journal={Nature Communications}, volume={15}, number={1}, pages={6572}, year={2024}, publisher={Nature Publishing Group UK London} } Paper link: https://www.nature.com/articles/s41467-024-50835-7 Related Publications -------------------- Hybrid Lens Design ^^^^^^^^^^^^^^^^^^ **dflens: Differentiable Pipeline for Hybrid Refractive-Diffractive Lens Design** .. code-block:: bibtex @article{wang2024dflens, title={dflens: A Differentiable Pipeline for Hybrid Refractive-Diffractive Lens Design}, author={Wang, Congli and Chen, Ni and Heidrich, Wolfgang}, journal={arXiv preprint arXiv:2406.00834}, year={2024} } Paper link: https://arxiv.org/abs/2406.00834 Aberration-Aware Depth Estimation ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ **Aberration-Aware Depth-from-Focus** .. code-block:: bibtex @article{yang2023aberration, title={Aberration-aware depth-from-focus}, author={Yang, Xinge and Fu, Qiang and Heidrich, Wolfgang}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume={46}, number={3}, pages={1697--1711}, year={2023}, publisher={IEEE} } Paper link: https://ieeexplore.ieee.org/document/10209238 History of DeepLens ------------------- Evolution Timeline ^^^^^^^^^^^^^^^^^^ **2021: Early Development** * Initial concept and prototyping * Basic ray tracing framework * Differentiable optimization proof-of-concept **2022: Core Features** * Comprehensive optical surface library * Wave optics integration * Sensor and ISP simulation * First automated lens designs **2023: Advanced Capabilities** * Aberration-aware imaging (TPAMI 2023) * Neural surrogate models (PSFNet) * End-to-end optimization framework * Multi-wavelength support **2024: Public Release** * Nature Communications publication * Open-source release * Hybrid refractive-diffractive support (SIGGRAPH Asia 2024) * Community building **2025: Ongoing Development** * Enhanced GPU acceleration * Distributed computing support * Polarization ray tracing * Non-sequential systems Key Milestones ^^^^^^^^^^^^^^ .. list-table:: :widths: 20 80 :header-rows: 1 * - Date - Milestone * - 2021 - Project initiated at KAUST * - 2022 - First fully automated lens design from scratch * - 2023 Jun - TPAMI paper on aberration-aware depth estimation * - 2024 Jul - Nature Communications paper published * - 2024 Aug - Open-source release on GitHub * - 2024 Dec - SIGGRAPH Asia paper on hybrid lenses * - 2025 - Community edition with extended features Contributors ------------ Core Team ^^^^^^^^^ * **Xinge Yang** - Project Lead, Main Developer * **Qiang Fu** - Optical Design Consultant * **Wolfgang Heidrich** - Principal Investigator Major Contributors ^^^^^^^^^^^^^^^^^^ * **Congli Wang** - Hybrid lens module * **Ni Chen** - Wave optics algorithms See full list at: https://github.com/singer-yang/DeepLens/graphs/contributors Acknowledgments --------------- Funding ^^^^^^^ This project was supported by: * King Abdullah University of Science and Technology (KAUST) * Visual Computing Center (VCC) * Computational Imaging Lab Collaborations ^^^^^^^^^^^^^^ We thank our collaborators: * MIT Media Lab * Stanford Computational Imaging Lab * Various industry partners Open Source Community ^^^^^^^^^^^^^^^^^^^^^ Special thanks to our open-source community for: * Bug reports and fixes * Feature suggestions * Documentation improvements * Testing and validation Awards and Recognition ---------------------- * **Nature Communications** - Featured article (2024) * **SIGGRAPH Asia** - Technical paper (2024) * **TPAMI** - Journal publication (2023) Media Coverage -------------- DeepLens has been featured in: * Nature Communications press release * KAUST Discovery magazine * Computer graphics and optics news outlets Research Using DeepLens ------------------------ If you have published research using DeepLens, let us know! We'd love to feature it here. Example applications: * Automated lens design for imaging systems * Computational photography research * Virtual reality optics * Smartphone camera optimization * Microscopy and scientific imaging * Automotive camera systems Contact ------- For academic collaborations: * **Email**: xinge.yang@kaust.edu.sa * **Lab**: Visual Computing Center, KAUST For commercial licensing: * **Email**: wolfgang.heidrich@kaust.edu.sa * **Website**: https://vccimaging.org Community --------- Join our community: * **GitHub**: https://github.com/singer-yang/DeepLens * **Slack**: https://join.slack.com/t/deeplens/shared_invite/zt-2wz3x2n3b-plRqN26eDhO2IY4r_gmjOw * **WeChat**: Contact singeryang1999 License ------- DeepLens is released under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). **What this means:** * ✓ Use for academic and research purposes * ✓ Modify and build upon the work * ✓ Share with attribution * ✗ Commercial use without permission For commercial licensing, please contact the authors. Future Directions ----------------- Planned Features ^^^^^^^^^^^^^^^^ * Extended material database * Tolerance analysis tools * Manufacturing interface * Cloud-based optimization * Real-time preview * VR/AR integration Research Directions ^^^^^^^^^^^^^^^^^^^ * Quantum optical systems * Freeform optics * Holographic displays * Neuromorphic imaging * Computational microscopy Get Involved ------------ Ways to contribute: * Use DeepLens in your research * Report bugs and issues * Suggest new features * Contribute code * Write documentation * Share your designs See :doc:`contributing` for details. See Also -------- * :doc:`../index` - Documentation home * :doc:`contributing` - How to contribute * :doc:`code_of_conduct` - Community guidelines