English(EN) Robust Promptable Video Object Segmentation

新的基准和MoGA方法增强了视频对象分割的鲁棒性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-12 11:55

研究人员推出了一种新的鲁棒可提示视频对象分割（PVOS）基准和方法，解决了现有模型在输入损坏下的性能下降问题。他们提出的MoGA方法利用存储在内存中的对象特定表示来处理损坏并保持时间一致性。在新基准数据集上的实验表明，MoGA在提高各种损坏类型下的分割精度方面非常有效。 AI

影响为鲁棒视频对象分割建立了一个新的基准和基线方法，这对于在安全关键型应用中部署AI至关重要。

排序理由该集群包含一篇学术论文，详细介绍了一项特定计算机视觉任务的新基准和方法。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Suha Kwak · 2026-05-12 11:55

鲁棒可提示视频目标分割

The performance of promptable video object segmentation (PVOS) models substantially degrades under input corruptions, which prevents PVOS deployment in safety-critical domains. This paper offers the first comprehensive study on robust PVOS (RobustPVOS). We first construct a new, …