63 citations · 87 across the 7 of their papers we have counts for
Showing 2023 · cs.CVShow all
3 papers · 2 filters
cs.CV2023★ 4 cited
Task-Driven Lens Design
Xinge Yang, Qiang Fu, Yunfeng Nie +1
Classical lens design minimizes optical aberrations to produce sharp images, but is typically decoupled from downstream computer vision tasks. Existing end-to-end optical design le…
cs.CV2023
Aberration-Aware Depth-from-Focus
Xinge Yang, Qiang Fu, Mohammed Elhoseiny +1
Computer vision methods for depth estimation usually use simple camera models with idealized optics. For modern machine learning approaches, this creates an issue when attempting t…
cs.CV2023★ 63 cited
Curriculum Learning for ab initio Deep Learned Refractive Optics
Xinge Yang, Qiang Fu, Wolfgang Heidrich
Deep optical optimization has recently emerged as a new paradigm for designing computational imaging systems using only the output image as the objective. However, it has been limi…