9 citations · 16 across the 7 of their papers we have counts for
7 papers
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…
Magic3DSketch: Create Colorful 3D Models From Sketch-Based 3D Modeling Guided by Text and Language-Image Pre-Training
Ying Zang, Yidong Han, Chaotao Ding +2
The requirement for 3D content is growing as AR/VR application emerges. At the same time, 3D modelling is only available for skillful experts, because traditional methods like Comp…
Deep3DSketch+: Obtaining Customized 3D Model by Single Free-Hand Sketch through Deep Learning
Ying Zang, Chenglong Fu, Tianrun Chen +3
As 3D models become critical in today's manufacturing and product design, conventional 3D modeling approaches based on Computer-Aided Design (CAD) are labor-intensive, time-consumi…
Deep3DSketch+\+: High-Fidelity 3D Modeling from Single Free-hand Sketches
Ying Zang, Chaotao Ding, Tianrun Chen +2
The rise of AR/VR has led to an increased demand for 3D content. However, the traditional method of creating 3D content using Computer-Aided Design (CAD) is a labor-intensive and s…
Reality3DSketch: Rapid 3D Modeling of Objects from Single Freehand Sketches
Tianrun Chen, Chaotao Ding, Lanyun Zhu +4
The emerging trend of AR/VR places great demands on 3D content. However, most existing software requires expertise and is difficult for novice users to use. In this paper, we aim t…