Scientific publications

At Visual Intelligence we work across our innovation areas to extract knowledge from large volumes of visual data more efficiently through automatic and intelligent data analysis. The work to address the core research challenges in deep learning: working with limited training data, utilizing context and dependencies, providing explainability, confidence and uncertainty, are important in all the innovation areas.

Featured blog posts

On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering

March 6, 2023
By
Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael Kampffmeyer.

Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings

March 6, 2023
By
Daniel J. Trosten*, Rwiddhi Chakraborty*, Sigurd Løkse, Kristoffer Knutsen Wickstrøm, Robert Jenssen, Michael Kampffmeyer (* indicates equal contribution)

All publications

ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design

By authors:

Xujie Zhang, Yu Sha, Michael Kampffmeyer, Zhenyu Xie, Zequn Jie, Chengwen Huang, Jianqing Peng, Xiaodan Liang

Published in:

ACM Multimedia (ACM MM 2022)

on

August 11, 2022

Multi-modal land cover mapping of remote sensing images using pyramid attention and gated fusion networks

By authors:

Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg

Published in:

International Journal of Remote Sensing, 2022

on

July 1, 2022

Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images

By authors:

Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu

Published in:

International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2022)

on

June 30, 2022

Principle of Relevant Information for Graph Sparsification

By authors:

Shujian Yu, Francesco Alesiani, Wenzhe Yin, Robert Jenssen and Jose C. Principe

Published in:

Conference on Uncertainty in Artificial Intelligence (UAI) 2022

on

May 20, 2022

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

By authors:

Luigi Tommaso Luppino, Mads Adrian Hansen, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Robert Jenssen and Stian Normann Anfinsen

Published in:

IEEE Transactions on Neural Networks and Learning Systems 2022

on

May 12, 2022

Mitral Annulus Segmentation and Anatomical Orientation Detection in TEE Images Using Periodic 3D CNN

By authors:

Børge Solli Andreassen, David Völgyes, Eigil Samset, Anne H. Schistad Solberg

Published in:

IEEE Access, Engineering in Medicine and Biology Section

on

May 10, 2022

Demonstrating the Risk of Imbalanced Datasets in Chest X-Ray Image-Based Diagnostics by Prototypical Relevance Propagation

By authors:

Srishti Gautam, Marina M. -C. Höhne, Stine Hansen, Robert Jenssen and Michael Kampffmeyer

Published in:

IEEE 19th International Symposium on Biomedical Imaging (ISBI), Kolkata, India, 2022

on

April 26, 2022

A mammography classification model trained from image labels only

By authors:

Fredrik Dahl, Marit Holden, Olav Brautaset and Line Eikvil

Published in:

Vol. 3 (2022): Proceedings of the Northern Lights Deep Learning Workshop 2022

on

March 28, 2022

Toward Scalable and Unified Example-Based Explanation and Outlier Detection

By authors:

Penny Chong, Ngai-Man Cheung, Yuval Elovici, Alexander Binder

Published in:

IEEE Transactions on Image Processing, vol. 31, pp. 525-540, 2022

on

March 11, 2022

M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretraining

By authors:

Xiao Dong, Xunlin Zhan, Yangxin Wu, Yunchao Wei, Michael C. Kampffmeyer, Xiaoyong Wei, Minlong Lu, Yaowei Wang, Xiaodan Liang

Published in:

Conference on Computer Vision and Pattern Recognition (CVPR), 2022

on

March 3, 2022

Other publications

annual reports