Search Results for author: Utsav Garg

Found 6 papers, 3 papers with code

Let's Go Shopping (LGS) -- Web-Scale Image-Text Dataset for Visual Concept Understanding

no code implementations9 Jan 2024 Yatong Bai, Utsav Garg, Apaar Shanker, Haoming Zhang, Samyak Parajuli, Erhan Bas, Isidora Filipovic, Amelia N. Chu, Eugenia D Fomitcheva, Elliot Branson, Aerin Kim, Somayeh Sojoudi, Kyunghyun Cho

Vision and vision-language applications of neural networks, such as image classification and captioning, rely on large-scale annotated datasets that require non-trivial data-collecting processes.

Image Captioning Image Classification +3

On the Performance of Multimodal Language Models

no code implementations4 Oct 2023 Utsav Garg, Erhan Bas

Instruction-tuned large language models (LLMs) have demonstrated promising zero-shot generalization capabilities across various downstream tasks.

Benchmarking Binary Classification +4

Fabrik: An Online Collaborative Neural Network Editor

no code implementations27 Oct 2018 Utsav Garg, Viraj Prabhu, Deshraj Yadav, Ram Ramrakhya, Harsh Agrawal, Dhruv Batra

We present Fabrik, an online neural network editor that provides tools to visualize, edit, and share neural networks from within a browser.

NAG: Network for Adversary Generation

1 code implementation CVPR 2018 Konda Reddy Mopuri, Utkarsh Ojha, Utsav Garg, R. Venkatesh Babu

Our trained generator network attempts to capture the distribution of adversarial perturbations for a given classifier and readily generates a wide variety of such perturbations.

CNN Fixations: An unraveling approach to visualize the discriminative image regions

2 code implementations22 Aug 2017 Konda Reddy Mopuri, Utsav Garg, R. Venkatesh Babu

We demonstrate through a variety of applications that our approach is able to localize the discriminative image locations across different network architectures, diverse vision tasks and data modalities.

Caption Generation Image Captioning +1

Fast Feature Fool: A data independent approach to universal adversarial perturbations

1 code implementation18 Jul 2017 Konda Reddy Mopuri, Utsav Garg, R. Venkatesh Babu

In this paper, for the first time, we propose a novel data independent approach to generate image agnostic perturbations for a range of CNNs trained for object recognition.

Object Recognition

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