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20172023
most citedAnomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels

164 citations · 413 across the 15 of their papers we have counts for

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10 papers · 1 filter

cs.CV2021

Reconsidering Representation Alignment for Multi-view Clustering

Daniel J. Trosten, Sigurd Løkse, Robert Jenssen +1

Aligning distributions of view representations is a core component of today's state of the art models for deep multi-view clustering. However, we identify several drawbacks with na…

cs.CV2020

SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation

Qinghui Liu, Michael Kampffmeyer, Robert Jenssen +1

Capturing global contextual representations by exploiting long-range pixel-pixel dependencies has shown to improve semantic segmentation performance. However, how to do this effici…

cs.CV20204 cited

Self-Constructing Graph Convolutional Networks for Semantic Labeling

Qinghui Liu, Michael Kampffmeyer, Robert Jenssen +1

Graph Neural Networks (GNNs) have received increasing attention in many fields. However, due to the lack of prior graphs, their use for semantic labeling has been limited. Here, we…

cs.CV20203 cited

Multi-view Self-Constructing Graph Convolutional Networks with Adaptive Class Weighting Loss for Semantic Segmentation

Qinghui Liu, Michael Kampffmeyer, Robert Jenssen +1

We propose a novel architecture called the Multi-view Self-Constructing Graph Convolutional Networks (MSCG-Net) for semantic segmentation. Building on the recently proposed Self-Co…

cs.CV20208 cited

Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images

Luigi T. Luppino, Mads A. Hansen, Michael Kampffmeyer +4

Image translation with convolutional autoencoders has recently been used as an approach to multimodal change detection in bitemporal satellite images. A main challenge is the align…

cs.CV2020

Dense Dilated Convolutions Merging Network for Land Cover Classification

Qinghui Liu, Michael Kampffmeyer, Robert Jessen +1

Land cover classification of remote sensing images is a challenging task due to limited amounts of annotated data, highly imbalanced classes, frequent incorrect pixel-level annotat…