149 citations · 155 across the 6 of their papers we have counts for
7 papers
Robustness Analysis on Foundational Segmentation Models
Madeline Chantry Schiappa, Shehreen Azad, Sachidanand VS +4
Due to the increase in computational resources and accessibility of data, an increase in large, deep learning models trained on copious amounts of multi-modal data using self-super…
Probing Conceptual Understanding of Large Visual-Language Models
Madeline Schiappa, Raiyaan Abdullah, Shehreen Azad +4
In recent years large visual-language (V+L) models have achieved great success in various downstream tasks. However, it is not well studied whether these models have a conceptual g…
SVGraph: Learning Semantic Graphs from Instructional Videos
Madeline C. Schiappa, Yogesh S. Rawat
In this work, we focus on generating graphical representations of noisy, instructional videos for video understanding. We propose a self-supervised, interpretable approach that doe…
Robustness Analysis of Video-Language Models Against Visual and Language Perturbations
Madeline C. Schiappa, Shruti Vyas, Hamid Palangi +2
Joint visual and language modeling on large-scale datasets has recently shown good progress in multi-modal tasks when compared to single modal learning. However, robustness of thes…
Large-scale Robustness Analysis of Video Action Recognition Models
Madeline Chantry Schiappa, Naman Biyani, Prudvi Kamtam +4
We have seen a great progress in video action recognition in recent years. There are several models based on convolutional neural network (CNN) and some recent transformer based ap…
Self-Supervised Learning for Videos: A Survey
Madeline C. Schiappa, Yogesh S. Rawat, Mubarak Shah
The remarkable success of deep learning in various domains relies on the availability of large-scale annotated datasets. However, obtaining annotations is expensive and requires gr…