activity
20182022
most citedDeep Exemplar Networks for VQA and VQG

1 citations · 2 across the 6 of their papers we have counts for

collaborators

15 papers

cs.CV2022

Barlow constrained optimization for Visual Question Answering

Abhishek Jha, Badri N. Patro, Luc Van Gool +1

Visual question answering is a vision-and-language multimodal task, that aims at predicting answers given samples from the question and image modalities. Most recent methods focus…

cs.CV2021

Collaborative Learning to Generate Audio-Video Jointly

Vinod K Kurmi, Vipul Bajaj, Badri N Patro +3

There have been a number of techniques that have demonstrated the generation of multimedia data for one modality at a time using GANs, such as the ability to generate images, video…

cs.LG2021

Do Not Forget to Attend to Uncertainty while Mitigating Catastrophic Forgetting

Vinod K Kurmi, Badri N. Patro, Venkatesh K. Subramanian +1

One of the major limitations of deep learning models is that they face catastrophic forgetting in an incremental learning scenario. There have been several approaches proposed to t…

cs.CV2020

Uncertainty based Class Activation Maps for Visual Question Answering

Badri N. Patro, Mayank Lunayach, Vinay P. Namboodiri

Understanding and explaining deep learning models is an imperative task. Towards this, we propose a method that obtains gradient-based certainty estimates that also provide visual…

cs.CV2020

Deep Bayesian Network for Visual Question Generation

Badri N. Patro, Vinod K. Kurmi, Sandeep Kumar +1

Generating natural questions from an image is a semantic task that requires using vision and language modalities to learn multimodal representations. Images can have multiple visua…

cs.CV2020

Robust Explanations for Visual Question Answering

Badri N. Patro, Shivansh Pate, Vinay P. Namboodiri

In this paper, we propose a method to obtain robust explanations for visual question answering(VQA) that correlate well with the answers. Our model explains the answers obtained th…