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Shrisudhan Govindarajan

4 accepted papers

2026

Semantic Foam: Unifying Spatial and Semantic Scene Decomposition

CVPR 2026

Modern scene reconstruction methods, such as 3D Gaussian Splatting, deliver photo-realistic novel view synthesis at real-time speeds, yet their adoption in interactive graphics applications has been limited. A major bottleneck is the difficulty of interacting with these representations compared to t

Cited by 0SourceScholar
2025

Radiant Foam: Real-Time Differentiable Ray Tracing

ICCV 2025poster

Research on differentiable scene representations is consistently moving towards more efficient, real-time models. Recently, this has led to the popularization of splatting methods, which eschew the traditional ray-based rendering of radiance fields in favor of rasterization. This has yielded a signi…

Cited by 0SourcePDFScholar
2024

BANF: Band-Limited Neural Fields for Levels of Detail Reconstruction

CVPR 2024poster

Largely due to their implicit nature neural fields lack a direct mechanism for filtering as Fourier analysis from discrete signal processing is not directly applicable to these representations. Effective filtering of neural fields is critical to enable level-of-detail processing in downstream applic…

Cited by 3SourcePDFScholar
2022

Synthesizing Light Field Video from Monocular Video

ECCV 2022poster

"The hardware challenges associated with light-field(LF) imaging has made it difficult for consumers to access its benefits like applications in post-capture focus and aperture control. Learning-based techniques which solve the ill-posed problem of LF reconstruction from sparse (1, 2 or 4) views hav…