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Vitali Petsiuk
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RISE: Randomized Input Sampling for Explanation of Black-box Models. arxiv 2018
V Petsiuk, A Das, K Saenko
British Machine Vision Conference (BMVC), 2018
637*2018
Black-box explanation of object detectors via saliency maps
V Petsiuk, R Jain, V Manjunatha, VI Morariu, A Mehra, V Ordonez, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
392021
RISE: Randomized Input Sampling for Explanation of Black-Box Models (2018)
V Petsiuk, A Das, K Saenko
arXiv preprint arXiv:1806.07421, 2018
282018
Why do these match? explaining the behavior of image similarity models
BA Plummer, MI Vasileva, V Petsiuk, K Saenko, D Forsyth
Proceedings of the European Conference on Computer Vision (ECCV), 652-669, 2020
142020
Guided Zoom: Questioning Network Evidence for Fine-grained Classification
SA Bargal, A Zunino, V Petsiuk, J Zhang, K Saenko, V Murino, S Sclaroff
British Machine Vision Conference (BMVC), 2019
132019
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
92021
RISE: Randomized input sampling for explanation of black-box models, arXiv
V Petsiuk, A Das, K Saenlo
arXiv preprint arXiv:1806.07421, 2018
92018
Are CNN predictions based on reasonable evidence?
SA Bargal, A Zunino, V Petsiuk, J Zhang, K Saenko, V Murino, S Sclaroff
CVPR Workshops 1, 2019
12019
Human Evaluation of Text-to-Image Models on a Multi-Task Benchmark
V Petsiuk, AE Siemenn, S Surbehera, Z Chin, K Tyser, G Hunter, ...
arXiv preprint arXiv:2211.12112, 2022
2022
Beyond the Visual Analysis of Deep Model Saliency
SA Bargal, A Zunino, V Petsiuk, J Zhang, V Murino, S Sclaroff, K Saenko
xxAI-Beyond Explainable AI: International Workshop, Held in Conjunction with …, 2022
2022
Explanatory visualizations for object detection
RB Jain, VI Morariu, V Petsiuk, V Manjunatha, A Mehra, VIO Roman
US Patent 11,227,159, 2022
2022
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