activity
20162022
most citedNeAT: Neural Adaptive Tomography

8 citations · 15 across the 5 of their papers we have counts for

collaborators

9 papers

cs.CV20221 cited

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…

cs.CV20221 cited

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…

cs.CV20228 cited

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…

eess.IV20213 cited

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…

eess.IV20212 cited

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…

eess.IV2019

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…