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20192022
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cs.CV2022

Leveraging Self-Supervised Training for Unintentional Action Recognition

Enea Duka, Anna Kukleva, Bernt Schiele

Unintentional actions are rare occurrences that are difficult to define precisely and that are highly dependent on the temporal context of the action. In this work, we explore such…

cs.CV2021

Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration without Forgetting

Anna Kukleva, Hilde Kuehne, Bernt Schiele

Both generalized and incremental few-shot learning have to deal with three major challenges: learning novel classes from only few samples per class, preventing catastrophic forgett…

cs.CV2020

Learning Interactions and Relationships between Movie Characters

Anna Kukleva, Makarand Tapaswi, Ivan Laptev

Interactions between people are often governed by their relationships. On the flip side, social relationships are built upon several interactions. Two strangers are more likely to…

cs.CV2019

Utilizing Temporal Information in Deep Convolutional Network for Efficient Soccer Ball Detection and Tracking

Anna Kukleva, Mohammad Asif Khan, Hafez Farazi +1

Soccer ball detection is identified as one of the critical challenges in the RoboCup competition. It requires an efficient vision system capable of handling the task of detection w…

cs.CV2019

Unsupervised learning of action classes with continuous temporal embedding

Anna Kukleva, Hilde Kuehne, Fadime Sener +1

The task of temporally detecting and segmenting actions in untrimmed videos has seen an increased attention recently. One problem in this context arises from the need to define and…