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20222026
most citedNeAT: Neural Adaptive Tomography

8 citations · 10 across the 5 of their papers we have counts for

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Showing cs.CVShow all

6 papers · 1 filter

cs.CV2026

Lightweight Neural Framework for Robust 3D Volume and Surface Estimation from Multi-View Images

Diego E. Farchione, Ramzi Idoughi, Peter Wonka

Accurate volume and surface area estimation is critical for diverse applications, from marine ecology to medical diagnostics. However, existing methods often suffer from high compu…

cs.CV2026

Any Resolution Any Geometry: From Multi-View To Multi-Patch

Wenqing Cui, Zhenyu Li, Mykola Lavreniuk +4

Joint estimation of surface normals and depth is essential for holistic 3D scene understanding, yet high-resolution prediction remains difficult due to the trade-off between preser…

cs.CV2025

No Mesh, No Problem: Estimating Coral Volume and Surface from Sparse Multi-View Images

Diego Eustachio Farchione, Ramzi Idoughi, Peter Wonka

Effective reef monitoring requires the quantification of coral growth via accurate volumetric and surface area estimates, which is a challenging task due to the complex morphology…

cs.CV2024

DissolveStereo: Coarse Depth Injection for Zero-Shot Stereo Video Generation

Jian Shi, Qian Wang, Zhenyu Li +3

Generating high-quality stereo videos requires consistent depth perception and temporal coherence across frames. Despite advances in image and video synthesis using diffusion model…

cs.CV2022★ 1 cited

Neural Adaptive SCEne Tracing

Rui Li, Darius Rückert, Yuanhao Wang +2

Neural rendering with implicit neural networks has recently emerged as an attractive proposition for scene reconstruction, achieving excellent quality albeit at high computational…

cs.CV2022★ 8 cited

NeAT: Neural Adaptive Tomography

Darius Rückert, Yuanhao Wang, Rui Li +2

In this paper, we present Neural Adaptive Tomography (NeAT), the first adaptive, hierarchical neural rendering pipeline for multi-view inverse rendering. Through a combination of n…