The article introduces a novel method called Point-VOS for Video Object Segmentation (VOS). Traditional VOS methods require dense per-object mask annotations which are time-consuming and costly. Point-VOS, however, utilizes a…
Continue readingThe paper introduces a new method for self-supervised video object segmentation (VOS) by leveraging inherent structural dependencies in DINO-pretrained Transformers. Instead of resorting to auxiliary modalities or iterative slot attention,…
Continue readingThe article presents a new method for video object segmentation (VOS) that uses sketches as references, rather than photo masks or language expressions. The authors argue that sketches are a…
Continue readingThe article introduces Cutie, a video object segmentation (VOS) network that employs object-level memory reading for better results. Unlike previous VOS systems that use bottom-up pixel-level memory reading, Cutie uses…
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