InfiniSplat: Implicit Gaussian Decoding for Large-Baseline Monocular View Synthesis

Conditionally Accepted to SIGGRAPH Asia 2026 (Journal Track)

Jiawei Wang^1* Hao Yu^1* Yongzhen Hu¹ Xinyi Yang¹ Tao Ni² Xin Zhan² Junbo Chen^2†

Xiaowei Zhou³ Ruizhen Hu⁴ Sida Peng^1†

¹Zhejiang University ²UDeer.ai ³State Key Laboratory of CAD&CG, Zhejiang University ⁴Shenzhen University

^*Equal contribution ^†Corresponding authors

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Code

Hugging Face Demo

TL;DR

InfiniSplat is a feed-forward single-image 3D Gaussian Splatting framework for large-baseline novel view synthesis.
It moves Gaussian generation from pixel-aligned image grids toward surface-aligned supports guided by monocular geometry.
A query-conditioned implicit Gaussian decoder predicts Gaussian attributes on sampled supports, producing more coherent surfaces under large viewpoint changes.

Demo

Qualitative Visualization

In-the-wild

In-the-wild RGB input

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Qualitative Comparison

RGB qualitative comparison under large viewpoint changes. InfiniSplat-RGB produces fewer visible cracks and more coherent scene structures than feed-forward baselines.

With sparse LiDAR points as additional input, InfiniSplat-LiDAR produces substantially better novel-view rendering quality than ADGaussian.

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InfiniSplat V2

Multi-view Feed-Forward Gaussian Splatting

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Citation

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