| Top-Down Neural Attention by Excitation Backprop J Zhang, SA Bargal, Z Lin, J Brandt, X Shen, S Sclaroff International Journal of Computer Vision, 2017 | 1036 | 2017 |
| Moments in time dataset: one million videos for event understanding M Monfort, A Andonian, B Zhou, K Ramakrishnan, SA Bargal, T Yan, ... IEEE transactions on pattern analysis and machine intelligence 42 (2), 502-508, 2019 | 638 | 2019 |
| Emotion Recognition in the Wild from Videos using Images SA Bargal, E Barsoum, C Canton Ferrer, C Zhang International Conference on Multimodal Interaction (ICMI), 2016 | 213 | 2016 |
| NBDT: neural-backed decision trees A Wan, L Dunlap, D Ho, J Yin, S Lee, H Jin, S Petryk, SA Bargal, ... International Conference on Learning Representations, 2020 | 187 | 2020 |
| Disrupting Deepfakes: Adversarial Attacks Against Conditional Image Translation Networks and Facial Manipulation Systems N Ruiz, SA Bargal, S Sclaroff ECCVW, 2020 | 116 | 2020 |
| MIHash: Online Hashing with Mutual Information F Cakir, K He, SA Bargal, S Sclaroff International Conference on Computer Vision, 2017 | 113 | 2017 |
| Hashing as tie-aware learning to rank K He, F Cakir, SA Bargal, S Sclaroff Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 106 | 2018 |
| Hashing with mutual information F Cakir, K He, SA Bargal, S Sclaroff IEEE transactions on pattern analysis and machine intelligence 41 (10), 2424 …, 2019 | 105 | 2019 |
| Do Less and Achieve More: Training CNNs for Action Recognition Utilizing Action Images from the Web S Ma, SA Bargal, J Zhang, L Sigal, S Sclaroff Journal of Pattern Recognition, 2017 | 94 | 2017 |
| Online Supervised Hashing F Cakir, SA Bargal, S Sclaroff Computer Vision and Image Understanding, 2016 | 76 | 2016 |
| Excitation backprop for RNNs SA Bargal, A Zunino, D Kim, J Zhang, V Murino, S Sclaroff Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 61 | 2018 |
| DMCL: Distillation Multiple Choice Learning for Multimodal Action Recognition NC Garcia, SA Bargal, V Ablavsky, P Morerio, V Murino, S Sclaroff Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2019 | 58* | 2019 |
| Explainable deep classification models for domain generalization A Zunino, SA Bargal, R Volpi, M Sameki, J Zhang, S Sclaroff, V Murino, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 46 | 2021 |
| Zerowaste dataset: Towards deformable object segmentation in cluttered scenes D Bashkirova, M Abdelfattah, Z Zhu, J Akl, F Alladkani, P Hu, V Ablavsky, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 40 | 2022 |
| Student engagement dataset K Delgado, JM Origgi, T Hasanpoor, H Yu, D Allessio, I Arroyo, W Lee, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 36 | 2021 |
| Excitation Dropout: Encouraging plasticity in deep neural networks A Zunino, SA Bargal, P Morerio, J Zhang, S Sclaroff, V Murino International Journal of Computer Vision, 1-14, 2018 | 33 | 2018 |
| Image-based Ear Biometric Smartphone App for Patient Identification in Field Settings SA Bargal, A Welles, CR Chan, S Howes, S Sclaroff, E Ragan, C Johnson, ... International Conference on Computer Vision Theory and Applications (VISAPP), 2015 | 28 | 2015 |
| Guided zoom: Zooming into network evidence to refine fine-grained model decisions SA Bargal, A Zunino, V Petsiuk, J Zhang, K Saenko, V Murino, S Sclaroff IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (11), 4196 …, 2021 | 19 | 2021 |
| Guided Zoom: Questioning network evidence for fine-grained classification SA Bargal, A Zunino, V Petsiuk, J Zhang, K Saenko, V Murino, S Sclaroff The British Machine Vision Conference, 2019 | 19 | 2019 |
| Protecting against image translation deepfakes by leaking universal perturbations from black-box neural networks N Ruiz, SA Bargal, S Sclaroff arXiv preprint arXiv:2006.06493, 2020 | 12 | 2020 |
Stan SclaroffDean of Arts & Sciences, Professor of Computer Science, Boston UniversityVerified email at bu.edu
