1 citations · 1 across the 5 of their papers we have counts for
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Spatial 3D-LLM: Exploring Spatial Awareness in 3D Vision-Language Models
Xiaoyan Wang, Zeju Li, Yifan Xu +5
New era has unlocked exciting possibilities for extending Large Language Models (LLMs) to tackle 3D vision-language tasks. However, most existing 3D multimodal LLMs (MLLMs) rely on…
Argus: Leveraging Multiview Images for Improved 3-D Scene Understanding With Large Language Models
Yifan Xu, Chao Zhang, Hanqi Jiang +6
Advancements in foundation models have made it possible to conduct applications in various downstream tasks. Especially, the new era has witnessed a remarkable capability to extend…
R3GS: Gaussian Splatting for Robust Reconstruction and Relocalization in Unconstrained Image Collections
Xu yan, Zhaohui Wang, Rong Wei +3
We propose R3GS, a robust reconstruction and relocalization framework tailored for unconstrained datasets. Our method uses a hybrid representation during training. Each anchor comb…
MMGDreamer: Mixed-Modality Graph for Geometry-Controllable 3D Indoor Scene Generation
Zhifei Yang, Keyang Lu, Chao Zhang +9
Controllable 3D scene generation has extensive applications in virtual reality and interior design, where the generated scenes should exhibit high levels of realism and controllabi…
3DMIT: 3D Multi-modal Instruction Tuning for Scene Understanding
Zeju Li, Chao Zhang, Xiaoyan Wang +4
The remarkable potential of multi-modal large language models (MLLMs) in comprehending both vision and language information has been widely acknowledged. However, the scarcity of 3…