41 citations · 46 across the 7 of their papers we have counts for
8 papers · 1 filter
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…
IBD: Alleviating Hallucinations in Large Vision-Language Models via Image-Biased Decoding
Lanyun Zhu, Deyi Ji, Tianrun Chen +3
Despite achieving rapid developments and with widespread applications, Large Vision-Language Models (LVLMs) confront a serious challenge of being prone to generating hallucinations…
RESMatch: Referring Expression Segmentation in a Semi-Supervised Manner
Ying Zang, Chenglong Fu, Runlong Cao +5
Referring expression segmentation (RES), a task that involves localizing specific instance-level objects based on free-form linguistic descriptions, has emerged as a crucial fronti…
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…