9 papers
Towards Blind Lens Aberration Correction via Large LensLib Pre-training and Discrete Degradation Priors
Xiaolong Qian, Qi Jiang, Yao Gao +8
Emerging deep-learning-based lens library pre-training (LensLib-PT) pipeline offers a new avenue for blind lens aberration correction by training a universal neural network, demons…
Towards Universal Computational Aberration Correction in Photographic Cameras: A Comprehensive Benchmark Analysis
Xiaolong Qian, Qi Jiang, Yao Gao +5
Prevalent Computational Aberration Correction (CAC) methods are typically tailored to specific optical systems, leading to poor generalization and labor-intensive re-training for n…
Learning Latent Transmission and Glare Maps for Lens Veiling Glare Removal
Xiaolong Qian, Qi Jiang, Lei Sun +8
Beyond the commonly recognized optical aberrations, the imaging performance of simplified optical systems--including single-lens and metalens designs--is often further degraded by…
OPTIAGENT: A Physics-Driven Agentic Framework for Automated Optical Design
Yuyu Geng, Lei Sun, Yao Gao +6
Optical design is the process of configuring optical elements to precisely manipulate light for high-fidelity imaging. It is inherently a highly non-convex optimization problem tha…
OmniLens: Towards Universal Lens Aberration Correction via LensLib-to-Specific Domain Adaptation
Qi Jiang, Yao Gao, Shaohua Gao +7
Emerging universal Computational Aberration Correction (CAC) paradigms provide an inspiring solution to light-weight and high-quality imaging with a universal model trained on a le…
Seeing Clearly and Deeply: An RGBD Imaging Approach with a Bio-inspired Monocentric Design
Zongxi Yu, Xiaolong Qian, Shaohua Gao +4
Achieving high-fidelity, compact RGBD imaging presents a dual challenge: conventional compact optics struggle with RGB sharpness across the entire depth-of-field, while software-on…