activity
20152019
most citedDiscovering Human Interactions in Videos with Limited Data Labeling

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2019

A Robust Learning Approach to Domain Adaptive Object Detection

Mehran Khodabandeh, Arash Vahdat, Mani Ranjbar +1

Domain shift is unavoidable in real-world applications of object detection. For example, in self-driving cars, the target domain consists of unconstrained road environments which c…

stat.ML2018

Distribution Aware Active Learning

Arash Mehrjou, Mehran Khodabandeh, Greg Mori

Discriminative learning machines often need a large set of labeled samples for training. Active learning (AL) settings assume that the learner has the freedom to ask an oracle to l…

cs.CV2018

DIY Human Action Data Set Generation

Mehran Khodabandeh, Hamid Reza Vaezi Joze, Ilya Zharkov +1

The recent successes in applying deep learning techniques to solve standard computer vision problems has aspired researchers to propose new computer vision problems in different do…

cs.CV2017

Active Learning for Structured Prediction from Partially Labeled Data

Mehran Khodabandeh, Zhiwei Deng, Mostafa S. Ibrahim +2

We propose a general purpose active learning algorithm for structured prediction, gathering labeled data for training a model that outputs a set of related labels for an image or v…

cs.CV20152 cited

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…