April 30, 2024, 4:47 a.m. | Zicheng Zhang, Haoning Wu, Yingjie Zhou, Chunyi Li, Wei Sun, Chaofeng Chen, Xiongkuo Min, Xiaohong Liu, Weisi Lin, Guangtao Zhai

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.18203v1 Announce Type: new
Abstract: Although large multi-modality models (LMMs) have seen extensive exploration and application in various quality assessment studies, their integration into Point Cloud Quality Assessment (PCQA) remains unexplored. Given LMMs' exceptional performance and robustness in low-level vision and quality assessment tasks, this study aims to investigate the feasibility of imparting PCQA knowledge to LMMs through text supervision. To achieve this, we transform quality labels into textual descriptions during the fine-tuning phase, enabling LMMs to derive quality rating …

abstract application arxiv assessment cloud cs.ai cs.cv exploration integration lmm lmms low performance quality robustness studies study tasks type vision

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