71 citations · 98 across the 32 of their papers we have counts for
3 papers · 1 filter
RED++ : Data-Free Pruning of Deep Neural Networks via Input Splitting and Output Merging
Edouard Yvinec, Arnaud Dapogny, Matthieu Cord +1
Pruning Deep Neural Networks (DNNs) is a prominent field of study in the goal of inference runtime acceleration. In this paper, we introduce a novel data-free pruning protocol RED+…
Tackling Catastrophic Forgetting and Background Shift in Continual Semantic Segmentation
Arthur Douillard, Yifu Chen, Arnaud Dapogny +1
Deep learning approaches are nowadays ubiquitously used to tackle computer vision tasks such as semantic segmentation, requiring large datasets and substantial computational power.…
RED : Looking for Redundancies for Data-Free Structured Compression of Deep Neural Networks
Edouard Yvinec, Arnaud Dapogny, Matthieu Cord +1
Deep Neural Networks (DNNs) are ubiquitous in today's computer vision land-scape, despite involving considerable computational costs. The mainstream approaches for runtime accelera…