53 citations · 60 across the 10 of their papers we have counts for
18 papers
Heracles: A Hybrid SSM-Transformer Model for High-Resolution Image and Time-Series Analysis
Badri N. Patro, Suhas Ranganath, Vinay P. Namboodiri +1
Transformers have revolutionized image modeling tasks with adaptations like DeIT, Swin, SVT, Biformer, STVit, and FDVIT. However, these models often face challenges with inductive…
SpectFormer: Frequency and Attention is what you need in a Vision Transformer
Badri N. Patro, Vinay P. Namboodiri, Vijay Srinivas Agneeswaran
Vision transformers have been applied successfully for image recognition tasks. There have been either multi-headed self-attention based (ViT \cite{dosovitskiy2020image}, DeIT, \ci…
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…
Attentive Contractive Flow with Lipschitz-constrained Self-Attention
Avideep Mukherjee, Badri Narayan Patro, Vinay P. Namboodiri
Normalizing flows provide an elegant method for obtaining tractable density estimates from distributions by using invertible transformations. The main challenge is to improve the e…
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…
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…
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…
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…
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…
Revisiting Paraphrase Question Generator using Pairwise Discriminator
Badri N. Patro, Dev Chauhan, Vinod K. Kurmi +1
In this paper, we propose a method for obtaining sentence-level embeddings. While the problem of securing word-level embeddings is very well studied, we propose a novel method for…
Deep Exemplar Networks for VQA and VQG
Badri N. Patro, Vinay P. Namboodiri
In this paper, we consider the problem of solving semantic tasks such as `Visual Question Answering' (VQA), where one aims to answers related to an image and `Visual Question Gener…
Explanation vs Attention: A Two-Player Game to Obtain Attention for VQA
Badri N. Patro, Anupriy, Vinay P. Namboodiri
In this paper, we aim to obtain improved attention for a visual question answering (VQA) task. It is challenging to provide supervision for attention. An observation we make is tha…
Probabilistic framework for solving Visual Dialog
Badri N. Patro, Anupriy, Vinay P. Namboodiri
In this paper, we propose a probabilistic framework for solving the task of `Visual Dialog'. Solving this task requires reasoning and understanding of visual modality, language mod…
Dynamic Attention Networks for Task Oriented Grounding
Soumik Dasgupta, Badri N. Patro, Vinay P. Namboodiri
In order to successfully perform tasks specified by natural language instructions, an artificial agent operating in a visual world needs to map words, concepts, and actions from th…
Granular Multimodal Attention Networks for Visual Dialog
Badri N. Patro, Shivansh Patel, Vinay P. Namboodiri
Vision and language tasks have benefited from attention. There have been a number of different attention models proposed. However, the scale at which attention needs to be applied…
U-CAM: Visual Explanation using Uncertainty based Class Activation Maps
Badri N. Patro, Mayank Lunayach, Shivansh Patel +1
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…
Multimodal Differential Network for Visual Question Generation
Badri N. Patro, Sandeep Kumar, Vinod K. Kurmi +1
Generating natural questions from an image is a semantic task that requires using visual and language modality to learn multimodal representations. Images can have multiple visual…
Differential Attention for Visual Question Answering
Badri Patro, Vinay P. Namboodiri
In this paper we aim to answer questions based on images when provided with a dataset of question-answer pairs for a number of images during training. A number of methods have focu…