Kukleva, Anna Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society;
VidalMata_Joint_Visual-Temporal_Embedding_for_Unsupervised_Learning_of_Actions_in_Untrimmed_WACV_2021_paper.pdf (Preprint), 3MB
VidalMata, R. G., Scheirer, W. J., Kukleva, A., Cox, D., & Kuehne, H. (2021). Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences. In IEEE Winter Conference on Applications of Computer Vision (pp. 1238-1247). Computer Vision Foundation.