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CVPR Findings2026

UniVerse3D: Emerging Properties of Unified Multimodal Models in 3D Understanding and Generation

Junliang Ye, Zehuan Huang, Yansong Qu, Chunshi Wang, Yunhan Yang, Yang Li, Yawei Luo, Zhuo Chen, Sheng Lu, Jun Zhu, Chunchao Guo

Abstract

While unified multimodal models have made progress in the 2D domain, extending this paradigm to 3D remains in its nascent stages, hindered by data scarcity, high generative complexity, and the lack of well-aligned semantic representations. To address these challenges,

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Builds on29

  1. 3D-LLM: Injecting the 3D World into Large Language ModelsYining Hong, Haoyu Zhen, Peihao Chen, Shuhong Zheng et al.NeurIPS 2023 · 662 citations
  2. Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent RepresentationZibo Zhao, Wen Liu, Xin Chen, Xianfang Zeng et al.NeurIPS 2023 · 279 citations
  3. OmniGen2: Towards Instruction-Aligned Multimodal GenerationChenyuan Wu, Jiahao Wang, Pengfei Zheng, Ruiran Yan et al.CVPR 2026 · 231 citations
  4. Chat-Scene: Bridging 3D Scene and Large Language Models with Object IdentifiersHaifeng Huang, Yilun Chen, Zehan Wang, Rongjie Huang et al.NeurIPS 2024 · 230 citations
  5. 3DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion ModelsBiao Zhang, Jiapeng Tang, Matthias Nießner, Peter WonkaSIGGRAPH 2023 · 172 citations

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