Sub-image anomaly detection with deep pyramid correspondences N Cohen, Y Hoshen arXiv preprint arXiv:2005.02357, 2020 | 384 | 2020 |
Classification-Based Anomaly Detection for General Data L Bergman, Y Hoshen International Conference on Learning Representations (ICLR 2020), 2020 | 375 | 2020 |
Speech Acoustic Modeling from Raw Multichannel Waveforms Y Hoshen, R Weiss, KW Wilson IEEE International Conference on Acoustics, Speech and Signal Processing, 2015 | 276 | 2015 |
VAIN: Attentional Multi-agent Predictive Modeling Y Hoshen Advances in Neural Information Processing Systems (NIPS'17), 2017 | 275 | 2017 |
Processing multi-channel audio waveforms TN Sainath, RJ Weiss, KW Wilson, AW Senior, A Narayanan, Y Hoshen, ... US Patent 9,697,826, 2017 | 235 | 2017 |
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation T Reiss, N Cohen, L Bergman, Y Hoshen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 224 | 2021 |
Deep nearest neighbor anomaly detection L Bergman, N Cohen, Y Hoshen arXiv preprint arXiv:2002.10445, 2020 | 137 | 2020 |
Non-adversarial unsupervised word translation Y Hoshen, L Wolf EMNLP'18, 2018 | 123* | 2018 |
Dreamix: Video diffusion models are general video editors E Molad, E Horwitz, D Valevski, AR Acha, Y Matias, Y Pritch, Y Leviathan, ... arXiv preprint arXiv:2302.01329, 2023 | 118 | 2023 |
Mean-shifted contrastive loss for anomaly detection T Reiss, Y Hoshen AAAI'23, 2023 | 90 | 2023 |
Demystifying Inter-Class Disentanglement A Gabbay, Y Hoshen International Conference on Learning Representations (ICLR 2020), 2020 | 63* | 2020 |
Non-Adversarial Image Synthesis with Generative Latent Nearest Neighbors Y Hoshen, K Li, J Malik Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 63 | 2019 |
An Egocentric Look at Video Photographer Identity Y Hoshen, S Peleg IEEE Conference on Computer Vision and Pattern Recognition (CVPR'16), 2016 | 61* | 2016 |
An image is worth more than a thousand words: Towards disentanglement in the wild A Gabbay, N Cohen, Y Hoshen Advances in Neural Information Processing Systems, 2021, 2021 | 34 | 2021 |
Image shape manipulation from a single augmented training sample Y Vinker, E Horwitz, N Zabari, Y Hoshen Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 34* | 2021 |
Visual Learning of Arithmetic Operations Y Hoshen, S Peleg Thirtieth AAAI Conference on Artificial Intelligence (AAAI'16), 2016 | 34 | 2016 |
Power to peep-all: Inference attacks by malicious batteries on mobile devices P Lifshits, R Forte, Y Hoshen, M Halpern, M Philipose, M Tiwari, ... Proceedings on Privacy Enhancing Technologies, 2018 | 33 | 2018 |
Nam: Non-adversarial unsupervised domain mapping Y Hoshen, L Wolf Proceedings of the European Conference on Computer Vision (ECCV), 436-451, 2018 | 30* | 2018 |
Back to the feature: classical 3d features are (almost) all you need for 3d anomaly detection E Horwitz, Y Hoshen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 29* | 2023 |
Open-Vocabulary Semantic Segmentation Using Test-Time Distillation N Zabari, Y Hoshen Computer Vision–ECCV 2022 Workshops: Tel Aviv, Israel, October 23–27, 2022 …, 2022 | 29* | 2022 |