activity
20192023
most citedEmotion-Controllable Generalized Talking Face Generation

5 citations · 5 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2023

A Fusion of Variational Distribution Priors and Saliency Map Replay for Continual 3D Reconstruction

Sanchar Palit, Sandika Biswas

Single-image 3D reconstruction is a research challenge focused on predicting 3D object shapes from single-view images. This task requires significant data acquisition to predict bo…

cs.CV2023

Physically Plausible 3D Human-Scene Reconstruction from Monocular RGB Image using an Adversarial Learning Approach

Sandika Biswas, Kejie Li, Biplab Banerjee +2

Holistic 3D human-scene reconstruction is a crucial and emerging research area in robot perception. A key challenge in holistic 3D human-scene reconstruction is to generate a physi…

cs.CV2022★ 5 cited

Emotion-Controllable Generalized Talking Face Generation

Sanjana Sinha, Sandika Biswas, Ravindra Yadav +1

Despite the significant progress in recent years, very few of the AI-based talking face generation methods attempt to render natural emotions. Moreover, the scope of the methods is…

cs.CV2020

Identity-Preserving Realistic Talking Face Generation

Sanjana Sinha, Sandika Biswas, Brojeshwar Bhowmick

Speech-driven facial animation is useful for a variety of applications such as telepresence, chatbots, etc. The necessary attributes of having a realistic face animation are 1) aud…

cs.CV2019

Lifting 2d Human Pose to 3d : A Weakly Supervised Approach

Sandika Biswas, Sanjana Sinha, Kavya Gupta +1

Estimating 3d human pose from monocular images is a challenging problem due to the variety and complexity of human poses and the inherent ambiguity in recovering depth from the sin…