7 papers
PrivFedTalk: Privacy-Aware Federated Diffusion with Identity-Stable Adapters for Personalized Talking-Head Generation
Soumya Mazumdar, Vineet Kumar Rakesh, Tapas Samanta
Talking-head generation has advanced rapidly with diffusion-based generative models, but training usually depends on centralized face-video and speech datasets, raising major priva…
TempoSyncDiff: Distilled Temporally-Consistent Diffusion for Low-Latency Audio-Driven Talking Head Generation
Soumya Mazumdar, Vineet Kumar Rakesh
Diffusion models have recently advanced photorealistic human synthesis, although practical talking-head generation (THG) remains constrained by high inference latency, temporal ins…
BayesFusion-SDF: Probabilistic Signed Distance Fusion with View Planning on CPU
Soumya Mazumdar, Vineet Kumar Rakesh, Tapas Samanta
Key part of robotics, augmented reality, and digital inspection is dense 3D reconstruction from depth observations. Traditional volumetric fusion techniques, including truncated si…
VineetVC: Adaptive Video Conferencing Under Severe Bandwidth Constraints Using Audio-Driven Talking-Head Reconstruction
Vineet Kumar Rakesh, Soumya Mazumdar, Tapas Samanta +3
Intense bandwidth depletion within consumer and constrained networks has the potential to undermine the stability of real-time video conferencing: encoder rate management becomes s…
VedicTHG: Symbolic Vedic Computation for Low-Resource Talking-Head Generation in Educational Avatars
Vineet Kumar Rakesh, Ahana Bhattacharjee, Soumya Mazumdar +4
Talking-head avatars are increasingly adopted in educational technology to deliver content with social presence and improved engagement. However, many recent talking-head generatio…
Analysis of Hyperparameter Optimization Effects on Lightweight Deep Models for Real-Time Image Classification
Vineet Kumar Rakesh, Soumya Mazumdar, Tapas Samanta +2
Lightweight convolutional and transformer-based networks are increasingly preferred for real-time image classification, especially on resource-constrained devices. This study evalu…