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Sankeerth Durvasula

3 accepted papers

2025

ContraGS: Codebook-Condensed and Trainable Gaussian Splatting for Fast, Memory-Efficient Reconstruction

ICCV 2025accepted

3D Gaussian Splatting (3DGS) is a state-of-art technique to model real-world scenes with high quality and real-time rendering.Typically, a higher quality representation can be achieved by using a large number of 3D Gaussians. However, using large 3D Gaussian counts significantly increases the GPU de…

Cited by 0SourcePDFScholar
2025

DISORF: A Distributed Online 3D Reconstruction Framework for Mobile Robots

RA-L 2025

We present a framework, DISORF, to enable online 3D reconstruction and visualization of scenes captured by resource-constrained mobile robots and edge devices. To address the limited computing capabilities of edge devices and potentially limited network availability, we design a framework that effic

Cited by 0SourcecodeScholar
2023

Ev-Conv: Fast CNN Inference on Event Camera Inputs for High-Speed Robot Perception

RA-L 2023

Event cameras capture visual information with a high temporal resolution and a wide dynamic range. This enables capturing visual information at fine time granularities (e.g., microseconds) in rapidly changing environments. This makes event cameras highly useful for high-speed robotics tasks involvin

Cited by 1SourceScholar