8 citations · 22 across the 14 of their papers we have counts for
15 papers
Efficient Label Refinement for Face Parsing Under Extreme Poses Using 3D Gaussian Splatting
Ankit Gahlawat, Anirban Mukherjee, Dinesh Babu Jayagopi
Accurate face parsing under extreme viewing angles remains a significant challenge due to limited labeled data in such poses. Manual annotation is costly and often impractical at s…
Invisible Filters: Cultural Bias in Hiring Evaluations Using Large Language Models
Pooja S. B. Rao, Laxminarayen Nagarajan Venkatesan, Mauro Cherubini +1
Artificial Intelligence (AI) is increasingly used in hiring, with large language models (LLMs) having the potential to influence or even make hiring decisions. However, this raises…
The AI Model Risk Catalog: What Developers and Researchers Miss About Real-World AI Harms
Pooja S. B. Rao, Sanja Šćepanović, Dinesh Babu Jayagopi +2
We analyzed nearly 460,000 AI model cards from Hugging Face to examine how developers report risks. From these, we extracted around 3,000 unique risk mentions and built the \emph{A…
OMuSense-23: A Multimodal Dataset for Contactless Breathing Pattern Recognition and Biometric Analysis
Manuel Lage Cañellas, Le Nguyen, Anirban Mukherjee +6
In the domain of non-contact biometrics and human activity recognition, the lack of a versatile, multimodal dataset poses a significant bottleneck. To address this, we introduce th…
SemUV: Deep Learning based semantic manipulation over UV texture map of virtual human heads
Anirban Mukherjee, Venkat Suprabath Bitra, Vignesh Bondugula +2
Designing and manipulating virtual human heads is essential across various applications, including AR, VR, gaming, human-computer interaction and VFX. Traditional graphic-based app…
RID-TWIN: An end-to-end pipeline for automatic face de-identification in videos
Anirban Mukherjee, Monjoy Narayan Choudhury, Dinesh Babu Jayagopi
Face de-identification in videos is a challenging task in the domain of computer vision, primarily used in privacy-preserving applications. Despite the considerable progress achiev…