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cs.CV2024
Empowering Segmentation Ability to Multi-modal Large Language Models
Yuqi Yang, Peng-Tao Jiang, Jing Wang +4
Multi-modal large language models (MLLMs) can understand image-language prompts and demonstrate impressive reasoning ability. In this paper, we extend MLLMs' output by empowering M…
cs.CV2024
Multi-Task Dense Prediction via Mixture of Low-Rank Experts
Yuqi Yang, Peng-Tao Jiang, Qibin Hou +3
Previous multi-task dense prediction methods based on the Mixture of Experts (MoE) have received great performance but they neglect the importance of explicitly modeling the global…