119 citations · 170 across the 5 of their papers we have counts for
5 papers · 1 filter
Shifting Transformation Learning for Out-of-Distribution Detection
Sina Mohseni, Arash Vahdat, Jay Yadawa
Detecting out-of-distribution (OOD) samples plays a key role in open-world and safety-critical applications such as autonomous systems and healthcare. Recently, self-supervised rep…
Contrastive Learning for Weakly Supervised Phrase Grounding
Tanmay Gupta, Arash Vahdat, Gal Chechik +3
Phrase grounding, the problem of associating image regions to caption words, is a crucial component of vision-language tasks. We show that phrase grounding can be learned by optimi…
Semi-Supervised Semantic Image Segmentation with Self-correcting Networks
Mostafa S. Ibrahim, Arash Vahdat, Mani Ranjbar +1
Building a large image dataset with high-quality object masks for semantic segmentation is costly and time consuming. In this paper, we introduce a principled semi-supervised frame…
Hierarchical Deep Temporal Models for Group Activity Recognition
Mostafa S. Ibrahim, Srikanth Muralidharan, Zhiwei Deng +2
In this paper we present an approach for classifying the activity performed by a group of people in a video sequence. This problem of group activity recognition can be addressed by…
Discovering Human Interactions in Videos with Limited Data Labeling
Mehran Khodabandeh, Arash Vahdat, Guang-Tong Zhou +4
We present a novel approach for discovering human interactions in videos. Activity understanding techniques usually require a large number of labeled examples, which are not availa…