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PREDATOR: Registration of 3D Point Clouds with Low Overlap

Authors:  ShengyuHuang, ZanGojcic, MikhailUsvyatsov....
Published date-11/25/2020
Tasks:  DeepAttention, PointCloudRegistration

Abstract: We introduce PREDATOR, a model for pairwise point-cloud registration with deep attention to the overlap region. Different from previous work, our model is specifically designed to handle (also) point-cloud pairs …
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The Unreasonable Effectiveness of Encoder-Decoder Networks for Retinal Vessel Segmentation

Authors:  BjörnBrowatzki, Jörn-PhilippLies, ChristianWallraven....
Published date-11/25/2020
Tasks:  RetinalVesselSegmentation

Abstract: We propose an encoder-decoder framework for the segmentation of blood vessels in retinal images that relies on the extraction of large-scale patches at multiple image-scales during training. Experiments on three …
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Simple statistical methods for unsupervised brain anomaly detection on MRI are competitive to deep learning methods

Authors:  VictorSaase, HolgerWenz, ThomasGanslandt....
Published date-11/25/2020
Tasks:  AnomalyDetection

Abstract: Statistical analysis of magnetic resonance imaging (MRI) can help radiologists to detect pathologies that are otherwise likely to be missed. Deep learning (DL) has shown promise in modeling complex spatial …
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Physics-informed neural networks for myocardial perfusion MRI quantification

Authors:  RudolfL.M.vanHerten, AmedeoChiribiri, MarcelBreeuwer....
Published date-11/25/2020

Abstract: Tracer-kinetic models allow for the quantification of kinetic parameters such as blood flow from dynamic contrast-enhanced magnetic resonance (MR) images. Fitting the observed data with multi-compartment exchange models is desirable, …
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Attention Aware Cost Volume Pyramid Based Multi-view Stereo Network for 3D Reconstruction

Authors:  AnzhuYu, WenyueGuo, BingLiu....
Published date-11/25/2020
Tasks:  3DReconstruction

Abstract: We present an efficient multi-view stereo (MVS) network for 3D reconstruction from multiview images. While previous learning based reconstruction approaches performed quite well, most of them estimate depth maps at …
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BinPlay: A Binary Latent Autoencoder for Generative Replay Continual Learning

Authors:  KamilDeja, PawełWawrzyński, DanielMarczak....
Published date-11/25/2020
AutoEncoder
Generative Models
Tasks:  ContinualLearning

Abstract: We introduce a binary latent space autoencoder architecture to rehearse training samples for the continual learning of neural networks. The ability to extend the knowledge of a model with new …
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