9 citations · 13 across the 7 of their papers we have counts for
7 papers · 1 filter
4DVGGT-D: 4D Visual Geometry Transformer with Improved Dynamic Depth Estimation
Ying Zang, Xuanyi Liu, Yidong Han +9
Reconstructing dynamic 4D scenes from monocular videos is a fundamental yet challenging task. While recent 3D foundation models provide strong geometric priors, their performance s…
Robust 4D Visual Geometry Transformer with Uncertainty-Aware Priors
Ying Zang, Yidong Han, Chaotao Ding +8
Reconstructing dynamic 4D scenes is an important yet challenging task. While 3D foundation models like VGGT excel in static settings, they often struggle with dynamic sequences whe…
HD-VGGT: High-Resolution Visual Geometry Transformer
Tianrun Chen, Yuanqi Hu, Yidong Han +11
High-resolution imagery is essential for accurate 3D reconstruction, as many geometric details only emerge at fine spatial scales. Recent feed-forward approaches, such as the Visua…
From Air to Wear: Personalized 3D Digital Fashion with AR/VR Immersive 3D Sketching
Ying Zang, Yuanqi Hu, Xinyu Chen +7
In the era of immersive consumer electronics, such as AR/VR headsets and smart devices, people increasingly seek ways to express their identity through virtual fashion. However, ex…
Img2CAD: Conditioned 3D CAD Model Generation from Single Image with Structured Visual Geometry
Tianrun Chen, Chunan Yu, Yuanqi Hu +8
In this paper, we propose Img2CAD, the first approach to our knowledge that uses 2D image inputs to generate CAD models with editable parameters. Unlike existing AI methods for 3D…
SAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More
Tianrun Chen, Ankang Lu, Lanyun Zhu +7
The advent of large models, also known as foundation models, has significantly transformed the AI research landscape, with models like Segment Anything (SAM) achieving notable succ…