activity
20242026
collaborators

9 papers

cs.CV2026

HCIG: A Hierarchical Cross-Modal Incongruity Graph Network for Multimodal Sarcasm and Cyberbullying Detection

Bhavana Verma, Priyanka Meel, Dinesh Kumar Vishwakarma

Multimodal sarcasm and cyberbullying detection remain challenging because the intended meaning often emerges from incongruity between textual and visual information rather than fro…

cs.CV2025

Tex-ViT: A Generalizable, Robust, Texture-based dual-branch cross-attention deepfake detector

Deepak Dagar, Dinesh Kumar Vishwakarma

Deepfakes, which employ GAN to produce highly realistic facial modification, are widely regarded as the prevailing method. Traditional CNN have been able to identify bogus media, b…

cs.CL2024

MHS-STMA: Multimodal Hate Speech Detection via Scalable Transformer-Based Multilevel Attention Framework

Anusha Chhabra, Dinesh Kumar Vishwakarma

Social media has a significant impact on people's lives. Hate speech on social media has emerged as one of society's most serious issues in recent years. Text and pictures are two…

cs.CL2024

Hate Content Detection via Novel Pre-Processing Sequencing and Ensemble Methods

Anusha Chhabra, Dinesh Kumar Vishwakarma

Social media, particularly Twitter, has seen a significant increase in incidents like trolling and hate speech. Thus, identifying hate speech is the need of the hour. This paper in…

cs.CV2024

A Noise and Edge extraction-based dual-branch method for Shallowfake and Deepfake Localization

Deepak Dagar, Dinesh Kumar Vishwakarma

The trustworthiness of multimedia is being increasingly evaluated by advanced Image Manipulation Localization (IML) techniques, resulting in the emergence of the IML field. An effe…

cs.CV2024

Target-Dependent Multimodal Sentiment Analysis Via Employing Visual-to Emotional-Caption Translation Network using Visual-Caption Pairs

Ananya Pandey, Dinesh Kumar Vishwakarma

The natural language processing and multimedia field has seen a notable surge in interest in multimodal sentiment recognition. Hence, this study aims to employ Target-Dependent Mul…