Perceptual Image Anomaly Detection. - Nina Tuluptceva; Bart Bakker; Irina Fedulova; Anton Konushin (ACPR (1), 2019)

Anomaly Detection with Deep Perceptual Autoencoders. - Nina Tuluptceva; Bart Bakker; Irina Fedulova; Heinrich Schulz; Dmitry V. Dylov (CoRR, 2020)

Anomaly Detection in Medical Imaging With Deep Perceptual Autoencoders. - Nina Shvetsova; Bart Bakker; Irina Fedulova; Heinrich Schulz; Dmitry V. Dylov (IEEE Access, 2021)

Routing with Self-Attention for Multimodal Capsule Networks. - Kevin Duarte; Brian Chen 001; Nina Shvetsova; Andrew Rouditchenko; Samuel Thomas 001; Alexander H. Liu; David Harwath; James R. Glass; Hilde Kuehne; Mubarak Shah (CoRR, 2021)

Everything at Once - Multi-modal Fusion Transformer for Video Retrieval. - Nina Shvetsova; Brian Chen 001; Andrew Rouditchenko; Samuel Thomas 001; Brian Kingsbury; Rogério Feris; David Harwath; James R. Glass; Hilde Kuehne (CVPR, 2022)

Augmentation Learning for Semi-Supervised Classification. - Tim Frommknecht; Pedro Alves Zipf; Quanfu Fan; Nina Shvetsova; Hilde Kuehne (GCPR, 2022)

VL-Taboo: An Analysis of Attribute-based Zero-shot Capabilities of Vision-Language Models. - Felix Vogel; Nina Shvetsova; Leonid Karlinsky; Hilde Kuehne (CoRR, 2022)

MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images. - David Zimmerer; Peter M. Full; Fabian Isensee; Paul Jäger 002; Tim Adler; Jens Petersen; Gregor Köhler; Tobias Roß; Annika Reinke; Antanas Kascenas; Bjørn Sand Jensen; Alison Q. O'Neil; et al. (IEEE Trans. Medical Imaging, 2022)

Abstract: MOOD 2020 - A Public Benchmark for Out-of-distribution Detection and Localization on Medical Images. - David Zimmerer; Peter M. Full; Fabian Isensee; Paul Jäger 002; Tim Adler; Jens Petersen; Gregor Köhler; Tobias Roß; Annika Reinke; Antanas Kascenas; Bjørn Sand Jensen; Alison Q. O'Neil; et al. (Bildverarbeitung für die Medizin, 2023)

C2KD: Cross-Lingual Cross-Modal Knowledge Distillation for Multilingual Text-Video Retrieval. - Andrew Rouditchenko; Yung-Sung Chuang; Nina Shvetsova; Samuel Thomas 001; Rogério Feris; Brian Kingsbury; Leonid Karlinsky; David Harwath; Hilde Kuehne; James R. Glass (ICASSP, 2023)

MAtch, eXpand and Improve: Unsupervised Finetuning for Zero-Shot Action Recognition with Language Knowledge. - Wei Lin 019; Leonid Karlinsky; Nina Shvetsova; Horst Possegger; Mateusz Kozinski; Rameswar Panda; Rogério Feris; Hilde Kuehne; Horst Bischof (ICCV, 2023)

In-Style: Bridging Text and Uncurated Videos with Style Transfer for Text-Video Retrieval. - Nina Shvetsova; Anna Kukleva; Bernt Schiele; Hilde Kuehne (ICCV, 2023)

Learning by Sorting: Self-supervised Learning with Group Ordering Constraints. - Nina Shvetsova; Felix Petersen; Anna Kukleva; Bernt Schiele; Hilde Kuehne (ICCV, 2023)

Preserving Modality Structure Improves Multi-Modal Learning. - Sirnam Swetha; Mamshad Nayeem Rizve; Nina Shvetsova; Hilde Kuehne; Mubarak Shah (ICCV, 2023)

What, When, and Where? Self-Supervised Spatio- Temporal Grounding in Untrimmed Multi-Action Videos from Narrated Instructions. - Brian Chen 001; Nina Shvetsova; Andrew Rouditchenko; Daniel Kondermann; Samuel Thomas 001; Shih-Fu Chang; Rogério Feris; James R. Glass; Hilde Kuehne (CVPR, 2024)

HowToCaption: Prompting LLMs to Transform Video Annotations at Scale. - Nina Shvetsova; Anna Kukleva; Xudong Hong 002; Christian Rupprecht 001; Bernt Schiele; Hilde Kuehne (ECCV (56), 2024)

Unbiasing through Textual Descriptions: Mitigating Representation Bias in Video Benchmarks. - Nina Shvetsova; Arsha Nagrani; Bernt Schiele; Hilde Kuehne; Christian Rupprecht 001 (CVPR, 2025)

VideoGEM: Training-free Action Grounding in Videos. - Felix Vogel; Walid Bousselham; Anna Kukleva; Nina Shvetsova; Hilde Kuehne (CVPR, 2025)

M2SVid: End-to-End Inpainting and Refinement for Monocular-to-Stereo Video Conversion. - Nina Shvetsova; Goutam Bhat; Prune Truong; Hilde Kuehne; Federico Tombari (CoRR, 2025)