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Related publications (30)

Robust Isometric Non-Rigid Structure-From-Motion

Shaifali Parashar

Non-Rigid Structure-from-Motion (NRSfM) reconstructs a deformable 3D object from keypoint correspondences established between monocular 2D images. Current NRSfM methods lack statistical robustness, which is the ability to cope with correspondence errors. T ...

IEEE COMPUTER SOC2022

3D Common Corruptions and Data Augmentation

Amir Roshan Zamir, Oguzhan Fatih Kar, Andrei Atanov, Shuqing Teresa Yeo

We introduce a set of image transformations that can be used as corruptions to evaluate the robustness of models as well as data augmentation mechanisms for training neural networks. The primary distinction of the proposed transformations is that, unlike e ...

IEEE COMPUTER SOC2022

Natural-Looking Adversarial Examples From Freehand Sketches

Davide Nanni, Hakgu Kim

Deep neural networks (DNNs) have achieved great success in image classification and recognition compared to previous methods. However, recent works have reported that DNNs are very vulnerable to adversarial examples that are intentionally generated to misl ...

IEEE2022

CrossLoc: Scalable Aerial Localization Assisted by Multimodal Synthetic Data

Iordan Doytchinov, Qi Yan, Shanci Li, Jianhao Zheng

We present a visual localization system that learns to estimate camera poses in the real world with the help of synthetic data. Despite significant progress in recent years, most learning-based approaches to visual localization target at a single domain an ...

IEEE COMPUTER SOC2022

On the Scalability of Vision-based Drone Swarms in the Presence of Occlusions

Dario Floreano, Fabian Maximilian Schilling, Enrica Soria

Vision-based drone swarms have recently emerged as a promising alternative to address the fault-tolerance and flexibility limitations of centralized and communication-based aerial collective systems. Although most vision-based control algorithms rely on th ...

2022

Weakly Supervised Volumetric Image Segmentation with Deformed Templates

Pascal Fua, Pamuditha Udaranga Wickramasinghe, Patrick Moller Jensen, Mian Akbar Shah

There are many approaches to weakly-supervised training of networks to segment 2D images. By contrast, existing approaches to segmenting volumetric images rely on full-supervision of a subset of 2D slices of the 3D volume. We propose an approach to volume ...

Springer2022

Amplitude and phase reconstruction for Low-Energy Electron Holography of individual proteins

Hannah Julia Ochner

Single-molecule imaging methods are of importance in structural biology, and specifically in the imaging of proteins, since they can elucidate conformational variability and structural changes that might be lost in imaging methods relying on averaging proc ...

EPFL2022

Improving the Training of Compact Neural Networks for Visual Recognition

Shuxuan Guo

During the Artificial Intelligence (AI) revolution of the past decades, deep neural networks have been widely used and have achieved tremendous success in visual recognition. Unfortunately, deploying deep models is challenging because of their huge model s ...

EPFL2022

Radatron: Accurate Detection Using Multi-resolution Cascaded MIMO Radar

Haitham Al Hassanieh, Junfeng Guan, Seyedsohrab Madani, Saurabh Gupta, Waleed Ahmed

Millimeter wave (mmWave) radars are becoming a more popular sensing modality in self-driving cars due to their favorable characteristics in adverse weather. Yet, they currently lack sufficient spatial resolution for semantic scene understanding. In this pa ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

reference data for "A Critical Comparison of Annual Glare Simulation Methods"

Jan Wienold, Stephen William Wasilewski

Scene and reference results files for: "A Critical Comparison of Annual Glare Simulation Methods" Stephen Wasilewski, Jan Wienold, Marilyne Andersen 2022 Buildsim Nordic, Copenhagen Contents: 01-06*.tar.gz: reference simulation image archives, one ...

Zenodo2022

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