Omni-View: Unlocking How Generation Facilitates Understanding in Unified 3D Model based on Multiview images

• URL: http://arxiv.org/abs/2511.07222v1
• Date: Mon, 10 Nov 2025 15:44:48 GMT
• Title: Omni-View: Unlocking How Generation Facilitates Understanding in Unified 3D Model based on Multiview images
• Authors: JiaKui Hu, Shanshan Zhao, Qing-Guo Chen, Xuerui Qiu, Jialun Liu, Zhao Xu, Weihua Luo, Kaifu Zhang, Yanye Lu,
• Abstract summary: OmniView extends the unified understanding and generation of 3D scenes based on multi-view images.<n>It jointly models scene understanding, novel view synthesis, geometry estimation, enabling synergistic interaction between 3D scene understanding and generation tasks.
• Score: 40.459573512775556
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper presents Omni-View, which extends the unified multimodal understanding and generation to 3D scenes based on multiview images, exploring the principle that "generation facilitates understanding". Consisting of understanding model, texture module, and geometry module, Omni-View jointly models scene understanding, novel view synthesis, and geometry estimation, enabling synergistic interaction between 3D scene understanding and generation tasks. By design, it leverages the spatiotemporal modeling capabilities of its texture module responsible for appearance synthesis, alongside the explicit geometric constraints provided by its dedicated geometry module, thereby enriching the model's holistic understanding of 3D scenes. Trained with a two-stage strategy, Omni-View achieves a state-of-the-art score of 55.4 on the VSI-Bench benchmark, outperforming existing specialized 3D understanding models, while simultaneously delivering strong performance in both novel view synthesis and 3D scene generation.

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