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20242026
most citedNeural Inverse Rendering from Propagating Light

1 citations · 1 across the 3 of their papers we have counts for

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cs.CV2026

Velox: Learning Representations of 4D Geometry and Appearance

Anagh Malik, Dorian Chan, Xiaoming Zhao +3

We introduce a framework for learning latent representations of 4D objects which are descriptive, faithfully capturing object geometry and appearance; compressive, aiding in downst…

cs.CV2026

Dark3R: Learning Structure from Motion in the Dark

Andrew Y Guo, Anagh Malik, SaiKiran Tedla +7

We introduce Dark3R, a framework for structure from motion in the dark that operates directly on raw images with signal-to-noise ratios (SNRs) below dB -- a regime where conve…

cs.CV20251 cited

Neural Inverse Rendering from Propagating Light

Anagh Malik, Benjamin Attal, Andrew Xie +2

We present the first system for physically based, neural inverse rendering from multi-viewpoint videos of propagating light. Our approach relies on a time-resolved extension of neu…

cs.CV2024

Transientangelo: Few-Viewpoint Surface Reconstruction Using Single-Photon Lidar

Weihan Luo, Anagh Malik, David B. Lindell

We consider the problem of few-viewpoint 3D surface reconstruction using raw measurements from a lidar system. Lidar captures 3D scene geometry by emitting pulses of light to a tar…

cs.CV2024

Flying with Photons: Rendering Novel Views of Propagating Light

Anagh Malik, Noah Juravsky, Ryan Po +3

We present an imaging and neural rendering technique that seeks to synthesize videos of light propagating through a scene from novel, moving camera viewpoints. Our approach relies…

cs.CV2023

Transient Neural Radiance Fields for Lidar View Synthesis and 3D Reconstruction

Anagh Malik, Parsa Mirdehghan, Sotiris Nousias +2

Neural radiance fields (NeRFs) have become a ubiquitous tool for modeling scene appearance and geometry from multiview imagery. Recent work has also begun to explore how to use add…