most citedRef-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields

17 citations · 17 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CV2024

Flash Cache: Reducing Bias in Radiance Cache Based Inverse Rendering

Benjamin Attal, Dor Verbin, Ben Mildenhall +4

State-of-the-art techniques for 3D reconstruction are largely based on volumetric scene representations, which require sampling multiple points to compute the color arriving along…

cs.CV20241 cited

Binary Opacity Grids: Capturing Fine Geometric Detail for Mesh-Based View Synthesis

Christian Reiser, Stephan Garbin, Pratul P. Srinivasan +6

While surface-based view synthesis algorithms are appealing due to their low computational requirements, they often struggle to reproduce thin structures. In contrast, more expensi…

cs.CV20234 cited

MERF: Memory-Efficient Radiance Fields for Real-time View Synthesis in Unbounded Scenes

Christian Reiser, Richard Szeliski, Dor Verbin +5

Neural radiance fields enable state-of-the-art photorealistic view synthesis. However, existing radiance field representations are either too compute-intensive for real-time render…

cs.CV20233 cited

BakedSDF: Meshing Neural SDFs for Real-Time View Synthesis

Lior Yariv, Peter Hedman, Christian Reiser +5

We present a method for reconstructing high-quality meshes of large unbounded real-world scenes suitable for photorealistic novel view synthesis. We first optimize a hybrid neural…

cs.CV202117 cited

Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields

Dor Verbin, Peter Hedman, Ben Mildenhall +3

Neural Radiance Fields (NeRF) is a popular view synthesis technique that represents a scene as a continuous volumetric function, parameterized by multilayer perceptrons that provid…

cs.CV2016

Crossing the Road Without Traffic Lights: An Android-based Safety Device

Adi Perry, Dor Verbin, Nahum Kiryati

In the absence of pedestrian crossing lights, finding a safe moment to cross the road is often hazardous and challenging, especially for people with visual impairments. We present…