新型Transformer增强3D场景重建和边缘部署

报道来源 [4]

1. arXiv cs.AI TIER_1 English(EN) · Sicheng Zuo, Zixun Xie, Wenzhao Zheng, Shaoqing Xu, Fang Li, Shengyin Jiang, Long Chen, Zhi-Xin Yang, Jiwen Lu · 2026-06-04 04:00

   DVGT: Driving Visual Geometry Transformer

   arXiv:2512.16919v2 Announce Type: replace-cross Abstract: Perceiving and reconstructing 3D scene geometry from visual inputs is crucial for autonomous driving. However, there still lacks a driving-targeted dense geometry perception model that can adapt to different scenarios and …

2. arXiv cs.CV TIER_1 English(EN) · Yibin Zhao, Yihan Pan, Jun Nan, Wenli Yang, Liwei Chen, Jianjun Yi · 2026-06-02 04:00

   $\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer

   arXiv:2606.01573v1 Announce Type: new Abstract: Gaussian splatting has shown strong potential for 3D reconstruction and novel view synthesis. However, most existing methods require accurate camera parameters and per-scene optimization, while feed-forward methods with pixel-aligne…

3. arXiv cs.CV TIER_1 English(EN) · Zhizhen Pan, Hesong Wang, Huan Wang · 2026-06-01 04:00

   QVGGT: Post-Training Quantized Visual Geometry Grounded Transformer

   arXiv:2605.31124v1 Announce Type: new Abstract: Estimating 3D attributes directly from images has advanced rapidly with the Visual Geometry Grounded Transformer (VGGT), which predicts camera parameters, depth maps, and point clouds in a single forward pass. However, its 1.2B-para…

4. arXiv cs.CV TIER_1 English(EN) · Huan Wang · 2026-05-29 10:32

   QVGGT: Post-Training Quantized Visual Geometry Grounded Transformer

   Estimating 3D attributes directly from images has advanced rapidly with the Visual Geometry Grounded Transformer (VGGT), which predicts camera parameters, depth maps, and point clouds in a single forward pass. However, its 1.2B-parameter scale severely limits deployment on resour…