Srinidhi Hegde

Graduate Researcher
University of Maryland College Park

I am a research assistant at UMIACS working with Prof. Matthias Zwicker on efficient neural rendering solutions for point cloud visualization. My broader research interests lie at the intersection of 3D Vision and Computer Graphics with applications to mixed reality (AR/VR/XR) and scientific visualization. I previously worked at TCS Research with Dr. Lovekesh Vig and Ms. Ramya Hebbalaguppe on designing deep learning solutions for AR. I completed my undergraduate study in Computer Science and Engineering at IIITD where I collaborated with Prof. Saket Anand and Prof. Ojaswa Sharma on scene reconstruction and procedural modeling.

CV (as of Sep-2024).

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Featured Publications

NARVis: Neural Accelerated Rendering for Real-Time Scientific Point Cloud Visualization

NARVis: Neural Accelerated Rendering for Real-Time Scientific Point Cloud Visualization

(Under Review)

A high-quality neural renderer for visualizing a variety of large scientific point clouds with low motion-to-photon latency.

Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework

Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework

ICASSP, 2020

Augmenting the knowledge distillation framework with sparsity inducing ability of variational inference to learn compact and sparser networks.

SmartOverlays: A Visual Saliency Driven Label Placement for Intelligent Human-Computer Interfaces

SmartOverlays: A Visual Saliency Driven Label Placement for Intelligent Human-Computer Interfaces

WACV, 2020

A situated visualization method for overlay placement in AR and video applications respecting proximity to the object of interest, non-occlusion, and aesthetics.

GestAR: Real Time Gesture Interaction for AR with Egocentric View

GestAR: Real Time Gesture Interaction for AR with Egocentric View

ISMAR, 2016

Proposes a method for real-time gesture interaction for AR with egocentric view.