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

August 20, 2023
By
Xujie Zhang, Binbin Yang, Michael C. Kampffmeyer, Wenqing Zhang, Shiyue Zhang, Guansong Lu, Liang Lin, Hang Xu, Xiaodan Liang

August 20, 2023
By
Haoyuan Li, Haoye Dong, Hanchao Jia, Dong Huang, Michael C. Kampffmeyer, Liang Lin, Xiaodan Liang

All publications

DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment

By authors:

Xujie Zhang, Binbin Yang, Michael C. Kampffmeyer, Wenqing Zhang, Shiyue Zhang, Guansong Lu, Liang Lin, Hang Xu, Xiaodan Liang

Published in:

ICCV 2023

on

August 20, 2023

Coordinate Transformer: Achieving Single-stage Multi-person Mesh Recovery from Videos,

By authors:

Haoyuan Li, Haoye Dong, Hanchao Jia, Dong Huang, Michael C. Kampffmeyer, Liang Lin, Xiaodan Liang

Published in:

ICCV 2023

on

August 20, 2023

SuperCM: Revisiting Clustering for Semi-Supervised Learning

By authors:

Durgesh Singh, Ahcéne Boubekki, Robert Jenssen, Michael C. Kampffmeyer

Published in:

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

on

June 4, 2023

Federated Learning under Covariate Shifts with Generalization Guarantees

By authors:

Ali Ramezani-Kebrya, Fanghui Liu, Thomas Pethick, Grigorios Chrysos, Volkan Cevher

Published in:

Transactions on Machine Learning Research

on

June 1, 2023

The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus

By authors:

Anna Hedström, Philine Lou Bommer, Kristoffer Knutsen Wickstrøm, Wojciech Samek, Sebastian Lapuschkin, Marina MC Höhne

Published in:

Transactions on Machine Learning Research (06/2023)

on

June 1, 2023

Distributed extra-gradient with optimal complexity and communication guarantees

By authors:

Ali Ramezani-Kebrya, Kimon Antonakopoulos, Igor Krawczuk, Justin Deschenaux, Volkan Cevher

Published in:

International Conference on Learning Representations ICLR 2023

on

May 1, 2023

Automatic Identification of Chemical Moieties

By authors:

Jonas Lederer, Michael Gastegger, Kristof T. Schütt, Michael Kampffmeyer, Klaus-Robert Müller, and Oliver T. Unke

Published in:

Physical Chemistry Chemical Physics 2023

on

April 27, 2023

Predicting Regions of Local Recurrence in Glioblastomas Using Voxel-Based Radiomic Features of Multiparametric Postoperative MRI

By authors:

Cepeda, Santiago and Luppino, Luigi Tommaso and Pérez-Núñez, Angel and Solheim, Ole and García-García, Sergio and Velasco-Casares, María and Karlberg, Anna and Eikenes, Live and Sarabia, Rosario and Arrese, Ignacio and Zamora, Tomás and Gonzalez, Pedro and Jiménez-Roldán, Luis and Kuttner, Samuel

Published in:

Cancers. 2023; 15(6):1894.

on

March 22, 2023

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

By authors:

Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael Kampffmeyer.

Published in:

CVPR 2023

on

March 6, 2023

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

By authors:

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

Published in:

CVPR 2023

on

March 6, 2023

Other publications

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