1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2024
OCC-MLLM-Alpha:Empowering Multi-modal Large Language Model for the Understanding of Occluded Objects with Self-Supervised Test-Time Learning
Shuxin Yang, Xinhan Di
There is a gap in the understanding of occluded objects in existing large-scale visual language multi-modal models. Current state-of-the-art multi-modal models fail to provide sati…
cs.CV2024★ 1 cited
OCC-MLLM:Empowering Multimodal Large Language Model For the Understanding of Occluded Objects
Wenmo Qiu, Xinhan Di
There is a gap in the understanding of occluded objects in existing large-scale visual language multi-modal models. Current state-of-the-art multimodal models fail to provide satis…