no code implementations • 24 Oct 2023 • Surbhi Mittal, Kartik Thakral, Richa Singh, Mayank Vatsa, Tamar Glaser, Cristian Canton Ferrer, Tal Hassner
However, machine and deep learning algorithms, popular in the AI community today, depend heavily on the data used during their development.
no code implementations • the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023 • Kartik Narayan, Harsh Agarwal, Kartik Thakral, Surbhi Mittal, Mayank Vatsa, Richa Singh
In this research, we emulate the real-world scenario of deepfake generation and spreading, and propose the DF-Platter dataset, which contains (i) both low-resolution and high-resolution deepfakes generated using multiple generation techniques and (ii) single-subject and multiple-subject deepfakes, with face images of Indian ethnicity.
no code implementations • 7 Nov 2022 • Surbhi Mittal, Kartik Thakral, Puspita Majumdar, Mayank Vatsa, Richa Singh
Since facial region localization is an essential task for all face recognition pipelines, it is imperative to analyze the presence of such bias in popular deep models.
no code implementations • 19 Sep 2022 • Kartik Narayan, Harsh Agarwal, Kartik Thakral, Surbhi Mittal, Mayank Vatsa, Richa Singh
In order to enable the research community to address these questions, this paper proposes DeePhy, a novel Deepfake Phylogeny dataset which consists of 5040 deepfake videos generated using three different generation techniques.
no code implementations • 3 Aug 2020 • Aakarsh Malhotra, Surbhi Mittal, Puspita Majumdar, Saheb Chhabra, Kartik Thakral, Mayank Vatsa, Richa Singh, Santanu Chaudhury, Ashwin Pudrod, Anjali Agrawal
Firstly, we present the COVID-19 Multi-Task Network which is an automated end-to-end network for COVID-19 screening.