3 citations · 6 across the 7 of their papers we have counts for
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cs.CV2024★ 3 cited
Customize Segment Anything Model for Multi-Modal Semantic Segmentation with Mixture of LoRA Experts
Chenyang Zhu, Bin Xiao, Lin Shi +2
The recent Segment Anything Model (SAM) represents a significant breakthrough in scaling segmentation models, delivering strong performance across various downstream applications i…
cs.CV2024
InstantSwap: Fast Customized Concept Swapping across Sharp Shape Differences
Chenyang Zhu, Kai Li, Yue Ma +5
Recent advances in Customized Concept Swapping (CCS) enable a text-to-image model to swap a concept in the source image with a customized target concept. However, the existing meth…
cs.CV2024★ 1 cited
MultiBooth: Towards Generating All Your Concepts in an Image from Text
Chenyang Zhu, Kai Li, Yue Ma +2
This paper introduces MultiBooth, a novel and efficient technique for multi-concept customization in image generation from text. Despite the significant advancements in customized…