1 code implementation • ICCV 2021 • Yuxin Hou, Eleonora Vig, Michael Donoser, Loris Bazzani
Interactive retrieval for online fashion shopping provides the ability of changing image retrieval results according to the user feedback.
no code implementations • 12 Jul 2020 • Seyed Majid Azimi, Corentin Henry, Lars Sommer, Arne Schumann, Eleonora Vig
We have defined two main tasks on this dataset: dense semantic segmentation and multi-class lane-marking prediction.
no code implementations • 7 Jul 2018 • Seyed Majid Azimi, Eleonora Vig, Reza Bahmanyar, Marco Körner, Peter Reinartz
During training, we minimize joint horizontal and oriented bounding box loss functions, as well as a novel loss that enforces oriented boxes to be rectangular.
Ranked #49 on Object Detection In Aerial Images on DOTA (using extra training data)
1 code implementation • CVPR 2016 • Saumya Jetley, Naila Murray, Eleonora Vig
Most saliency estimation methods aim to explicitly model low-level conspicuity cues such as edges or blobs and may additionally incorporate top-down cues using face or text detection.
no code implementations • 25 Aug 2016 • César Roberto de Souza, Adrien Gaidon, Eleonora Vig, Antonio Manuel López
Action recognition in videos is a challenging task due to the complexity of the spatio-temporal patterns to model and the difficulty to acquire and learn on large quantities of video data.
no code implementations • CVPR 2016 • Adrien Gaidon, Qiao Wang, Yohann Cabon, Eleonora Vig
We provide quantitative experimental evidence suggesting that (i) modern deep learning algorithms pre-trained on real data behave similarly in real and virtual worlds, and (ii) pre-training on virtual data improves performance.
no code implementations • 4 Aug 2015 • Adrien Gaidon, Eleonora Vig
We quantitatively measure the benefit of our domain adaptation strategy on the KITTI tracking benchmark and on a new dataset (PASCAL-to-KITTI) we introduce to study the domain mismatch problem in MOT.
no code implementations • CVPR 2014 • Eleonora Vig, Michael Dorr, David Cox
Our models outperform the state of the art on MIT1003, on which features and classifiers are learned.