activity
20182022
most citedExplaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Values Approximation

48 citations · 80 across the 5 of their papers we have counts for

collaborators

11 papers

eess.IV20223 cited

Microdosing: Knowledge Distillation for GAN based Compression

Leonhard Helminger, Roberto Azevedo, Abdelaziz Djelouah +2

Recently, significant progress has been made in learned image and video compression. In particular the usage of Generative Adversarial Networks has lead to impressive results in th…

eess.IV20201 cited

Blind Image Restoration with Flow Based Priors

Leonhard Helminger, Michael Bernasconi, Abdelaziz Djelouah +2

Image restoration has seen great progress in the last years thanks to the advances in deep neural networks. Most of these existing techniques are trained using full supervision wit…

cs.CV202022 cited

Lossy Image Compression with Normalizing Flows

Leonhard Helminger, Abdelaziz Djelouah, Markus Gross +1

Deep learning based image compression has recently witnessed exciting progress and in some cases even managed to surpass transform coding based approaches that have been establishe…

cs.CV2020

Enriching Video Captions With Contextual Text

Philipp Rimle, Pelin Dogan, Markus Gross

Understanding video content and generating caption with context is an important and challenging task. Unlike prior methods that typically attempt to generate generic video captions…

cs.LG20206 cited

Shapley Value as Principled Metric for Structured Network Pruning

Marco Ancona, Cengiz Öztireli, Markus Gross

Structured pruning is a well-known technique to reduce the storage size and inference cost of neural networks. The usual pruning pipeline consists of ranking the network internal f…

cs.CV2019

Neural Sequential Phrase Grounding (SeqGROUND)

Pelin Dogan, Leonid Sigal, Markus Gross

We propose an end-to-end approach for phrase grounding in images. Unlike prior methods that typically attempt to ground each phrase independently by building an image-text embeddin…