output
20022026
most citedMethods for Interpreting and Understanding Deep Neural Networks

2.8k citations

Showing 2022 · cs.CVShow all

11 papers · 2 filters

cs.CV2022★ 20 cited

Fast Event-based Optical Flow Estimation by Triplet Matching

Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego

Event cameras are novel bio-inspired sensors that offer advantages over traditional cameras (low latency, high dynamic range, low power, etc.). Optical flow estimation methods that…

cs.CV2022★ 18 cited

A Fast Geometric Regularizer to Mitigate Event Collapse in the Contrast Maximization Framework

Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego

Event cameras are emerging vision sensors and their advantages are suitable for various applications such as autonomous robots. Contrast maximization (CMax), which provides state-o…

cs.CV2022★ 12 cited

Generative Reasoning Integrated Label Noise Robust Deep Image Representation Learning

Gencer Sumbul, Begüm Demir

The development of deep learning based image representation learning (IRL) methods has attracted great attention for various image understanding problems. Most of these methods req…

cs.CV2022★ 2 cited

Let's Enhance: A Deep Learning Approach to Extreme Deblurring of Text Images

Theophil Trippe, Martin Genzel, Jan Macdonald +1

This work presents a novel deep-learning-based pipeline for the inverse problem of image deblurring, leveraging augmentation and pre-training with synthetic data. Our results build…

cs.CV2022★ 4 cited

Advanced Deep Learning Architectures for Accurate Detection of Subsurface Tile Drainage Pipes from Remote Sensing Images

Tom-Lukas Breitkopf, Leonard W. Hackel, Mahdyar Ravanbakhsh +4

Subsurface tile drainage pipes provide agronomic, economic and environmental benefits. By lowering the water table of wet soils, they improve the aeration of plant roots and ultima…

cs.CV2022★ 1 cited

Image-based Detection of Surface Defects in Concrete during Construction

Dominik Kuhnke, Monika Kwiatkowski, Olaf Hellwich

Defects increase the cost and duration of construction projects as they require significant inspection and documentation efforts. Automating defect detection could significantly re…