AI RESEARCH
ELVIS: Enhance Low-Light for Video Instance Segmentation in the Dark
arXiv CS.CV
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ArXi:2512.01495v2 Announce Type: replace Video instance segmentation (VIS) for low-light content remains highly challenging for both humans and machines alike, due to noise, blur and other adverse conditions. The lack of large-scale annotated datasets and the limitations of current synthetic pipelines, particularly in modeling temporal degradations, further hinder progress. Moreover, existing VIS methods are not robust to the degradations found in low-light videos and, consequently, perform poorly even after finetuning. In this paper, we