VVGT: Visual Volume-Grounded Transformer

Fuente: arXiv
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Main Authors: Wang, Yuxuan, Li, Qibiao, Cai, Youcheng
Format: Preprint
Published: 2026
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author Wang, Yuxuan
Li, Qibiao
Cai, Youcheng
author_facet Wang, Yuxuan
Li, Qibiao
Cai, Youcheng
contents Volumetric visualization has long been dominated by Direct Volume Rendering (DVR), which operates on dense voxel grids and suffers from limited scalability as resolution and interactivity demands increase. Recent advances in 3D Gaussian Splatting (3DGS) offer a representation-centric alternative; however, existing volumetric extensions still depend on costly per-scene optimization, limiting scalability and interactivity. We present VVGT (Visual Volume-Grounded Transformer), a feed-forward, representation-first framework that directly maps volumetric data to a 3D Gaussian Splatting representation, advancing a new paradigm for volumetric visualization beyond DVR. Unlike prior feed-forward 3DGS methods designed for surface-centric reconstruction, VVGT explicitly accounts for volumetric rendering, where each pixel aggregates contributions along a ray. VVGT employs a dual-transformer network and introduces Volume Geometry Forcing, an epipolar cross-attention mechanism that integrates multi-view observations into distributed 3D Gaussian primitives without surface assumptions. This design eliminates per-scene optimization while enabling accurate volumetric representations. Extensive experiments show that VVGT achieves high-quality visualization with orders-of-magnitude faster conversion, improved geometric consistency, and strong zero-shot generalization across diverse datasets, enabling truly interactive and scalable volumetric visualization. The code will be publicly released upon acceptance.
format Preprint
id arxiv_https___arxiv_org_abs_2604_12217
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle VVGT: Visual Volume-Grounded Transformer
Wang, Yuxuan
Li, Qibiao
Cai, Youcheng
Graphics
Volumetric visualization has long been dominated by Direct Volume Rendering (DVR), which operates on dense voxel grids and suffers from limited scalability as resolution and interactivity demands increase. Recent advances in 3D Gaussian Splatting (3DGS) offer a representation-centric alternative; however, existing volumetric extensions still depend on costly per-scene optimization, limiting scalability and interactivity. We present VVGT (Visual Volume-Grounded Transformer), a feed-forward, representation-first framework that directly maps volumetric data to a 3D Gaussian Splatting representation, advancing a new paradigm for volumetric visualization beyond DVR. Unlike prior feed-forward 3DGS methods designed for surface-centric reconstruction, VVGT explicitly accounts for volumetric rendering, where each pixel aggregates contributions along a ray. VVGT employs a dual-transformer network and introduces Volume Geometry Forcing, an epipolar cross-attention mechanism that integrates multi-view observations into distributed 3D Gaussian primitives without surface assumptions. This design eliminates per-scene optimization while enabling accurate volumetric representations. Extensive experiments show that VVGT achieves high-quality visualization with orders-of-magnitude faster conversion, improved geometric consistency, and strong zero-shot generalization across diverse datasets, enabling truly interactive and scalable volumetric visualization. The code will be publicly released upon acceptance.
title VVGT: Visual Volume-Grounded Transformer
topic Graphics
url https://arxiv.org/abs/2604.12217