activity
20192026
most citedHate-CLIPper: Multimodal Hateful Meme Classification based on Cross-modal Interaction of CLIP Features

3 citations · 4 across the 10 of their papers we have counts for

collaborators

11 papers

cs.CV2026

Binding Biometrics with AI Agent Identifiers for Delegation of Authority

Joseph Geo Benjamin, Anil K Jain, Karthik Nandakumar

The proliferation of agentic artificial intelligence (AI) systems has raised serious questions about the accountability for tasks performed by AI agents. Ideally, an AI agent must…

cs.CV2026

Intra-finger Variability of Diffusion-based Latent Fingerprint Generation

Noor Hussein, Anil K. Jain, Karthik Nandakumar

The primary goal of this work is to systematically evaluate the intra-finger variability of synthetic fingerprints (particularly latent prints) generated using a state-of-the-art d…

cs.CV2023

Evading Forensic Classifiers with Attribute-Conditioned Adversarial Faces

Fahad Shamshad, Koushik Srivatsan, Karthik Nandakumar

The ability of generative models to produce highly realistic synthetic face images has raised security and ethical concerns. As a first line of defense against such fake faces, dee…

cs.CV2023

CLIP2Protect: Protecting Facial Privacy using Text-Guided Makeup via Adversarial Latent Search

Fahad Shamshad, Muzammal Naseer, Karthik Nandakumar

The success of deep learning based face recognition systems has given rise to serious privacy concerns due to their ability to enable unauthorized tracking of users in the digital…

cs.CL2022★ 3 cited

Hate-CLIPper: Multimodal Hateful Meme Classification based on Cross-modal Interaction of CLIP Features

Gokul Karthik Kumar, Karthik Nandakumar

Hateful memes are a growing menace on social media. While the image and its corresponding text in a meme are related, they do not necessarily convey the same meaning when viewed in…

cs.CV2022★ 1 cited

Learning an Ensemble of Deep Fingerprint Representations

Akash Godbole, Karthik Nandakumar, Anil K. Jain

Deep neural networks (DNNs) have shown incredible promise in learning fixed-length representations from fingerprints. Since the representation learning is often focused on capturin…