Stamatios Georgoulis
@stam_g
Followers
126
Following
100
Media
0
Statuses
24
Research Engineer | 3D Computer Vision, Machine Learning, Computational Photography | Huawei, ETH Zurich
Zurich, Switzerland
Joined June 2011
RT @VcPatricia: 1/n Our last work on event-based image deblurring has won the best paper award in the #MIPI workshop at #ECCV2022. https://….
0
1
0
RT @dimtzionas: Motivated MSc/BSc students & prospective PhD candidates can always reach out to me -- plz see the contact instructions on m….
0
5
0
RT @Deep__AI: Multi-Bracket High Dynamic Range Imaging with Event Cameras.by Nico Messikommer et al. including @sta….
deepai.org
03/13/22 - Modern high dynamic range (HDR) imaging pipelines align and fuse multiple low dynamic range (LDR) images captured at different exp...
0
1
0
RT @svandenh1: Excited to be hosting the DeepMTL workshop on multi-task learning at @ICCV_2021 tomorrow. We have an excellent group of spea….
sites.google.com
0
7
0
RT @AntonObukhov1: Our #ICCV2021 paper on Adaptive Task-Relational Context, leveraging neural architecture search and attention mechanisms….
0
5
0
RT @davsca1: So honored that our #CVPR2021 on video frame interpolation with event cameras is on #twominutepapers! @DanielGehrig6 @StepanTu….
0
16
0
RT @AntonObukhov1: The source code of our #ICML 2020 paper "T-Basis: a Compact Representation for Neural Networks" is now on GitHub: https:….
github.com
T-Basis: a Compact Representation for Neural Networks - toshas/tbasis
0
1
0
RT @AntonObukhov1: I will present our latest #AISTATS work about sparse and stable CNN parameterizations (pinned) in the sparsity workshop….
0
3
0
RT @WGansbeke: We study how biases in the dataset affect contrastive pretraining and explore additional invariances. What if we use non-cur….
0
2
0
RT @Deep__AI: Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation.by Suman Saha et al. includ….
deepai.org
05/17/21 - We present an approach for encoding visual task relationships to improve model performance in an Unsupervised Domain Adaptation (U...
0
1
0
RT @AntonObukhov1: 1/ Our paper “Spectral Tensor Train Parameterization of Deep Learning Layers” about end-to-end neural network compressio….
0
10
0
RT @Deep__AI: Spectral Tensor Train Parameterization of Deep Learning Layers.by Anton Obukhov et al. including @sta….
deepai.org
03/07/21 - We study low-rank parameterizations of weight matrices with embedded spectral properties in the Deep Learning context. The low-ran...
0
1
0
RT @AntonObukhov1: Code packaging frenzy continues! Check out my latest python package, democratizing orthogonal transformations in #PyTorc….
github.com
Efficient Householder Transformation in PyTorch. Contribute to toshas/torch-householder development by creating an account on GitHub.
0
5
0
RT @svandenh1: We have updated our survey on multi-task learning for dense prediction tasks. The paper features an extensive literature rev….
github.com
PyTorch implementation of multi-task learning architectures, incl. MTI-Net (ECCV2020). - GitHub - SimonVandenhende/Multi-Task-Learning-PyTorch: PyTorch implementation of multi-task learning archit...
0
6
0
RT @menelaoskanakis: The codebase from our #ECCV2020 paper titled "Reparameterizing Convolutions for Incremental Multi-Task Learning withou….
0
7
0
RT @menelaoskanakis: Check out our #BMVC2020 paper "Automated Search for Resource-Efficient Branched Multi-Task Networks". We propose an ap….
0
1
0
RT @menelaoskanakis: Join us today for the poster session of our work "Reparameterizing Convolutions for Incremental Multi-Task Learning wi….
0
5
0
RT @menelaoskanakis: Our paper "Reparameterizing Convolutions for Incremental Multi-Task Learning without Task Interference" has been accep….
0
9
0