63 citations · 226 across the 21 of their papers we have counts for
23 papers
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…
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…
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…
Various Wavefront Sensing and Control Developments on the Santa Cruz Extreme AO Laboratory (SEAL) Testbed
Benjamin L. Gerard, Javier Perez-Soto, Vincent Chambouleyron +7
Ground-based high contrast imaging (HCI) and extreme adaptive optics (AO) technologies have advanced to the point of enabling direct detections of gas-giant exoplanets orbiting bey…
CRISPnet: Color Rendition ISP Net
Matheus Souza, Wolfgang Heidrich
Image signal processors (ISPs) are historically grown legacy software systems for reconstructing color images from noisy raw sensor measurements. They are usually composited of man…
Neural Adaptive SCEne Tracing
Rui Li, Darius Rückert, Yuanhao Wang +2
Neural rendering with implicit neural networks has recently emerged as an attractive proposition for scene reconstruction, achieving excellent quality albeit at high computational…
NeAT: Neural Adaptive Tomography
Darius Rückert, Yuanhao Wang, Rui Li +2
In this paper, we present Neural Adaptive Tomography (NeAT), the first adaptive, hierarchical neural rendering pipeline for multi-view inverse rendering. Through a combination of n…
Snapshot HDR Video Construction Using Coded Mask
Masheal Alghamdi, Qiang Fu, Ali Thabet +1
This paper study the reconstruction of High Dynamic Range (HDR) video from snapshot-coded LDR video. Constructing an HDR video requires restoring the HDR values for each frame and…
ISP-Agnostic Image Reconstruction for Under-Display Cameras
Miao Qi, Yuqi Li, Wolfgang Heidrich
Under-display cameras have been proposed in recent years as a way to reduce the form factor of mobile devices while maximizing the screen area. Unfortunately, placing the camera be…
Shape and Reflectance Reconstruction in Uncontrolled Environments by Differentiable Rendering
Rui Li, Guangmin Zang, Miao Qi +1
Simultaneous reconstruction of geometry and reflectance properties in uncontrolled environments remains a challenging problem. In this paper, we propose an efficient method to reco…
Diffractive lensless imaging with optimized Voronoi-Fresnel phase
Qiang Fu, Dong-Ming Yan, Wolfgang Heidrich
Lensless cameras are a class of imaging devices that shrink the physical dimensions to the very close vicinity of the image sensor by replacing conventional compound lenses with in…
Neural Étendue Expander for Ultra-Wide-Angle High-Fidelity Holographic Display
Ethan Tseng, Grace Kuo, Seung-Hwan Baek +8
Holographic displays can generate light fields by dynamically modulating the wavefront of a coherent beam of light using a spatial light modulator, promising rich virtual and augme…
Mask-ToF: Learning Microlens Masks for Flying Pixel Correction in Time-of-Flight Imaging
Ilya Chugunov, Seung-Hwan Baek, Qiang Fu +2
We introduce Mask-ToF, a method to reduce flying pixels (FP) in time-of-flight (ToF) depth captures. FPs are pervasive artifacts which occur around depth edges, where light paths f…
Single-shot Hyperspectral-Depth Imaging with Learned Diffractive Optics
Seung-Hwan Baek, Hayato Ikoma, Daniel S. Jeon +4
Imaging depth and spectrum have been extensively studied in isolation from each other for decades. Recently, hyperspectral-depth (HS-D) imaging emerges to capture both information…
Stochastic Convolutional Sparse Coding
Jinhui Xiong, Peter Richtárik, Wolfgang Heidrich
State-of-the-art methods for Convolutional Sparse Coding usually employ Fourier-domain solvers in order to speed up the convolution operators. However, this approach is not without…
Rethinking Learning-based Demosaicing, Denoising, and Super-Resolution Pipeline
Guocheng Qian, Yuanhao Wang, Jinjin Gu +4
Imaging is usually a mixture problem of incomplete color sampling, noise degradation, and limited resolution. This mixture problem is typically solved by a sequential solution that…
Coupled Fluid Density and Motion from Single Views
Marie-Lena Eckert, Wolfgang Heidrich, Nils Thuerey
We present a novel method to reconstruct a fluid's 3D density and motion based on just a single sequence of images. This is rendered possible by using powerful physical priors for…
Imaging with SPADs and DMDs: Seeing through Diffraction-Photons
Ibrahim Alsolami, Wolfgang Heidrich
This paper addresses the problem of imaging in the presence of diffraction-photons. Diffraction-photons arise from the low contrast ratio of DMDs (), and very much de…
Discriminative Transfer Learning for General Image Restoration
Lei Xiao, Felix Heide, Wolfgang Heidrich +2
Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational effi…
Deep Video Deblurring
Shuochen Su, Mauricio Delbracio, Jue Wang +3
Motion blur from camera shake is a major problem in videos captured by hand-held devices. Unlike single-image deblurring, video-based approaches can take advantage of the abundant…
MindX: Denoising Mixed Impulse Poisson-Gaussian Noise Using Proximal Algorithms
Mohamed Aly, Wolfgang Heidrich
We present a novel algorithm for blind denoising of images corrupted by mixed impulse, Poisson, and Gaussian noises. The algorithm starts by applying the Anscombe variance-stabiliz…
TRex: A Tomography Reconstruction Proximal Framework for Robust Sparse View X-Ray Applications
Mohamed Aly, Guangming Zang, Wolfgang Heidrich +1
We present TRex, a flexible and robust Tomographic Reconstruction framework using proximal algorithms. We provide an overview and perform an experimental comparison between the fam…
A Compressive Multi-Mode Superresolution Display
Felix Heide, James Gregson, Gordon Wetzstein +2
Compressive displays are an emerging technology exploring the co-design of new optical device configurations and compressive computation. Previously, research has shown how to impr…