no code implementations • 29 Sep 2021 • Dan Hendrycks, Steven Basart, Mantas Mazeika, Andy Zou, Joseph Kwon, Mohammadreza Mostajabi, Jacob Steinhardt
We conduct extensive experiments in these more realistic settings for out-of-distribution detection and find that a surprisingly simple detector based on the maximum logit outperforms prior methods in all the large-scale multi-class, multi-label, and segmentation tasks, establishing a simple new baseline for future work.
3 code implementations • 25 Nov 2019 • Dan Hendrycks, Steven Basart, Mantas Mazeika, Andy Zou, Joe Kwon, Mohammadreza Mostajabi, Jacob Steinhardt, Dawn Song
We conduct extensive experiments in these more realistic settings for out-of-distribution detection and find that a surprisingly simple detector based on the maximum logit outperforms prior methods in all the large-scale multi-class, multi-label, and segmentation tasks, establishing a simple new baseline for future work.
no code implementations • 30 Aug 2019 • Mohammadreza Mostajabi
We describe an approach to learning rich representations for images, that enables simple and effective predictors in a range of vision tasks involving spatially structured maps.
2 code implementations • 1 Aug 2019 • Igor Vasiljevic, Nick Kolkin, Shanyi Zhang, Ruotian Luo, Haochen Wang, Falcon Z. Dai, Andrea F. Daniele, Mohammadreza Mostajabi, Steven Basart, Matthew R. Walter, Gregory Shakhnarovich
We introduce DIODE, a dataset that contains thousands of diverse high resolution color images with accurate, dense, long-range depth measurements.
no code implementations • CVPR 2018 • Mohammadreza Mostajabi, Michael Maire, Gregory Shakhnarovich
Our technique is applicable when the ground-truth labels themselves exhibit internal structure; we derive a regularizer by learning an autoencoder over the set of annotations.
no code implementations • 6 Dec 2016 • Mohammadreza Mostajabi, Nicholas Kolkin, Gregory Shakhnarovich
We propose an approach for learning category-level semantic segmentation purely from image-level classification tags indicating presence of categories.
1 code implementation • CVPR 2015 • Mohammadreza Mostajabi, Payman Yadollahpour, Gregory Shakhnarovich
We introduce a purely feed-forward architecture for semantic segmentation.