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Approximation-based Threshold Optimization from Single Antenna to Massive SIMO Authentication


Aug 11, 2022
Stefan Roth, Aydin Sezgin, Roman Bessel, H. Vincent Poor


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Semantic Self-adaptation: Enhancing Generalization with a Single Sample


Aug 10, 2022
Sherwin Bahmani, Oliver Hahn, Eduard Zamfir, Nikita Araslanov, Daniel Cremers, Stefan Roth

* Code and models: https://github.com/visinf/self-adaptive 

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Diverse Image Captioning with Grounded Style


May 03, 2022
Franz Klein, Shweta Mahajan, Stefan Roth

* In Proceedings of the German Conference on Pattern Recognition (GCPR), Ed. by C. Bauckhage, J. Gall, and A. G. Schwing, Vol. 13024, Lecture Notes in Computer Science, Springer, 2021, pp. 421-436 
* In the 43rd DAGM German Conference on Pattern Recognition (GCPR) 2021 

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Fast Axiomatic Attribution for Neural Networks


Nov 15, 2021
Robin Hesse, Simone Schaub-Meyer, Stefan Roth

* To appear at NeurIPS*2021. Project page and code: https://visinf.github.io/fast-axiomatic-attribution 

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Dense Unsupervised Learning for Video Segmentation


Nov 11, 2021
Nikita Araslanov, Simone Schaub-Meyer, Stefan Roth

* To appear at NeurIPS*2021. Code: https://github.com/visinf/dense-ulearn-vos 

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PixelPyramids: Exact Inference Models from Lossless Image Pyramids


Oct 17, 2021
Shweta Mahajan, Stefan Roth

* To appear at ICCV 2021 

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xGQA: Cross-Lingual Visual Question Answering


Sep 13, 2021
Jonas Pfeiffer, Gregor Geigle, Aishwarya Kamath, Jan-Martin O. Steitz, Stefan Roth, Ivan Vulić, Iryna Gurevych


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TxT: Crossmodal End-to-End Learning with Transformers


Sep 09, 2021
Jan-Martin O. Steitz, Jonas Pfeiffer, Iryna Gurevych, Stefan Roth

* To appear at the 43rd DAGM German Conference on Pattern Recognition (GCPR) 2021 

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Self-Supervised Multi-Frame Monocular Scene Flow


May 05, 2021
Junhwa Hur, Stefan Roth

* To appear at CVPR 2021. Code available: https://github.com/visinf/multi-mono-sf 

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Self-supervised Augmentation Consistency for Adapting Semantic Segmentation


Apr 30, 2021
Nikita Araslanov, Stefan Roth

* To appear at CVPR 2021. Code: https://github.com/visinf/da-sac 

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