3 citations · 4 across the 3 of their papers we have counts for
3 papers
Partially-Supervised Novel Object Captioning Leveraging Context from Paired Data
Shashank Bujimalla, Mahesh Subedar, Omesh Tickoo
In this paper, we propose an approach to improve image captioning solution for images with novel objects that do not have caption labels in the training dataset. We refer to our ap…
Data augmentation to improve robustness of image captioning solutions
Shashank Bujimalla, Mahesh Subedar, Omesh Tickoo
In this paper, we study the impact of motion blur, a common quality flaw in real world images, on a state-of-the-art two-stage image captioning solution, and notice a degradation i…
B-SCST: Bayesian Self-Critical Sequence Training for Image Captioning
Shashank Bujimalla, Mahesh Subedar, Omesh Tickoo
Bayesian deep neural networks (DNNs) can provide a mathematically grounded framework to quantify uncertainty in predictions from image captioning models. We propose a Bayesian vari…