Mohammad Saeed Rad
École Polytechnique Fédérale de Lausanne
16 Papers
53 Citations
Mohammad Saeed Rad is an academic researcher from École Polytechnique Fédérale de Lausanne. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 7, co-authored 16 publications.
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Papers
SROBB: Targeted Perceptual Loss for Single Image Super-Resolution
Mohammad Saeed Rad,Behzad Bozorgtabar,Urs-Viktor Marti,Max Basler,Hazim Kemal Ekenel,Jean-Philippe Thiran +5 more
- 01 Oct 2019
TL;DR: In this paper, the authors optimize a deep network-based decoder with a targeted objective function that penalizes images at different semantic levels using the corresponding terms, which results in more realistic textures and sharper edges.
SynDeMo: Synergistic Deep Feature Alignment for Joint Learning of Depth and Ego-Motion
Behzad Bozorgtabar,Mohammad Saeed Rad,Dwarikanath Mahapatra,Jean-Philippe Thiran +3 more
- 27 Oct 2019
TL;DR: Extensive experiments demonstrate that the depth and ego-motion models surpass the state-of-the-art, unsupervised methods and compare favorably to early supervised deep models for geometric understanding.
A Computer Vision System to Localize and Classify Wastes on the Streets
Mohammad Saeed Rad,Andreas von Kaenel,Andre Droux,Francois Tieche,Nabil Ouerhani,Hazim Kemal Ekenel,Jean-Philippe Thiran +6 more
- 10 Jul 2017
TL;DR: A fully automated computer vision application for littering quantification based on images taken from the streets and sidewalks using a deep learning based framework to localize and classify different types of wastes.
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A Computer Vision System to Localize and Classify Wastes on the Streets
Mohammad Saeed Rad,Andreas von Kaenel,Andre Droux,Francois Tieche,Nabil Ouerhani,Hazim Kemal Ekenel,Jean-Philippe Thiran +6 more
TL;DR: In this paper, a fully automated computer vision application for littering quantification based on images taken from the streets and sidewalks is presented. But there was no waste dataset available, so they built their acquisition system mounted on a vehicle and collected images containing different types of wastes.
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Using Photorealistic Face Synthesis and Domain Adaptation to Improve Facial Expression Analysis
Behzad Bozorgtabar,Mohammad Saeed Rad,Hazim Kemal Ekenel,Jean-Philippe Thiran +3 more
- 14 May 2019
TL;DR: In this paper, a new attribute guided face image synthesis model is proposed to perform a translation between multiple image domains using a single model, and the model can learn from synthetic faces by matching the feature distributions between different domains while preserving each domain's characteristics.
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