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Michael Hirsch

8 accepted papers

2019

Learning an Event Sequence Embedding for Dense Event-Based Deep Stereo

ICCV 2019oral

Today, a frame-based camera is the sensor of choice for machine vision applications. However, these cameras, originally developed for acquisition of static images rather than for sensing of dynamic uncontrolled visual environments, suffer from high power consumption, data rate, latency and low dynam…

Cited by 112PDFcodeScholar
2018

Spatio-temporal Transformer Network for Video Restoration

ECCV 2018poster

State-of-the-art video restoration methods integrate optical flow estimation networks to utilize temporal information. However, these networks typically consider only a pair of consecutive frames and hence are not capable of capturing long-range temporal dependencies and fall short of establishing c…

Cited by 203SourcePDFScholar
2017

Automatic detection of motion artifacts in MR images using CNNS

ICASSP 2017accepted

Considerable practical interest exists in being able to automatically determine whether a recorded magnetic resonance image is affected by motion artifacts caused by patient movements during scanning. Existing approaches usually rely on the use of navigators or external sensors to detect and track p…

Cited by 0SourceScholar
2017

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis

ICCV 2017oral

Single image super-resolution is the task of inferring a high-resolution image from a single low-resolution input. Traditionally, the performance of algorithms for this task is measured using pixel-wise reconstruction measures such as peak signal-to-noise ratio (PSNR) which have been shown to correl…

Cited by 1263PDFScholar
2017

Online Video Deblurring via Dynamic Temporal Blending Network

ICCV 2017poster

State-of-the-art video deblurring methods are capable of removing non-uniform blur caused by unwanted camera shake and/or object motion in dynamic scenes. However, most existing methods are based on batch processing and thus need access to all recorded frames, rendering them computationally demandin…

Cited by 197PDFScholar