CrossScore: Towards Multi-View Image Evaluation and Scoring

arXiv:2404.14409v1 Announce Type: new
Abstract: We introduce a novel cross-reference image quality assessment method that effectively fills the gap in the image assessment landscape, complementing the array of established evaluation schemes -- ranging from full-reference metrics like SSIM, no-reference metrics such as NIQE, to general-reference metrics including FID, and Multi-modal-reference metrics, e.g., CLIPScore. Utilising a neural network with the cross-attention mechanism and a unique data collection pipeline from NVS optimisation, our method enables accurate image quality assessment without requiring ground …

abstract array arxiv assessment cs.cv evaluation gap general image landscape metrics modal multi-modal novel quality reference scoring type view