41 citations · 46 across the 7 of their papers we have counts for
7 papers
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…
Deep3DSketch+: Rapid 3D Modeling from Single Free-hand Sketches
Tianrun Chen, Chenglong Fu, Ying Zang +4
The rapid development of AR/VR brings tremendous demands for 3D content. While the widely-used Computer-Aided Design (CAD) method requires a time-consuming and labor-intensive mode…
Learning Gabor Texture Features for Fine-Grained Recognition
Lanyun Zhu, Tianrun Chen, Jianxiong Yin +2
Extracting and using class-discriminative features is critical for fine-grained recognition. Existing works have demonstrated the possibility of applying deep CNNs to exploit featu…
SAM Fails to Segment Anything? -- SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, Medical Image Segmentation, and More
Tianrun Chen, Lanyun Zhu, Chaotao Ding +6
The emergence of large models, also known as foundation models, has brought significant advancements to AI research. One such model is Segment Anything (SAM), which is designed for…