R Srinath — accepted AI-conference papers

2026

Turbo-GS: Accelerating 3D Gaussian Fitting for High-Resolution Radiance Fields

Ankit Dhiman, Tao Lu, R Srinath, Emre Arslan, Angela Xing, Yuanbo Xiangli +2

CVPR 2026

Novel-view synthesis plays a crucial role in computer vision with applications in 3D reconstruction, mixed reality, and robotics. Recent approaches, such as 3D Gaussian Splatting (3DGS), have emerged as state-of-the-art solutions, offering high-quality novel view synthesis in real time. However, tra

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2023

Strata-NeRF : Neural Radiance Fields for Stratified Scenes

Ankit Dhiman, R Srinath, Harsh Rangwani, Rishubh Parihar, Lokesh R Boregowda, Srinath Sridhar +1

ICCV 2023poster

Neural Radiance Fields (NeRF) approaches learn the underlying 3D representation of a scene and generate photo-realistic novel views with high fidelity. However, most proposed settings concentrate on 3D modelling a single object or a single level of a scene. However, in the real world, a person captu…

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