Video temporal grounding (VTG) aims to localize the start and end timestamps of the event described by a given query within an untrimmed video. Despite the strong open-world video understanding and recognition ability of video language large models (Vid-LLMs), outputting precise temporal grounding information remains challenging, since explicit temporal cues are scarce in untrimmed videos, and query-relevant entities are hard to track consistently across the video timeline. In this paper, we present \MarkIt{}, a training-free framework that transforms an input video into a query-conditioned marked video, which empowers Vid-LLMs to generate more reliable temporal localization predictions. The core component of \MarkIt{} is an annotation-free query-to-mask grounding bridge (Q2M-Bridge). Given a natural-language query, it automatically derives a compact set of canonical subject tags through linguistic parsing and normalization, then maps these tags to query-conditioned instance masks using text-conditioned open-vocabulary segmentation. The bridge also embeds lightweight semantic instance markers and a persistent frame index into each frame, effectively transforming long-range temporal reasoning into explicit visual cues for Vid-LLMs. \MarkIt{} adopts an inference-time plug-and-play design, needs no modifications to Vid-LLM weights, and is fully compatible with supervised fine-tuning. Experiments conducted on multiple mainstream moment retrieval and highlight detection benchmarks demonstrate that \MarkIt {} achieves state-of-the-art results, delivering consistent temporal grounding improvements across a wide range of existing models.

翻译：视频时间定位（VTG）旨在于未裁剪视频中定位给定查询所描述事件的起始与结束时间戳。尽管视频语言大模型（Vid-LLMs）具备强大的开放世界视频理解与识别能力，但由于未裁剪视频中显式时间线索稀缺，且查询相关实体难以在视频时间线上持续稳定追踪，输出精确的时间定位信息仍具挑战。本文提出MarkIt{}——一个无需训练框架，可将输入视频转换为查询条件化的标记视频，从而赋能Vid-LLMs生成更可靠的时间定位预测。MarkIt{}的核心组件为无标注查询到掩码定位桥梁（Q2M-Bridge）。对于自然语言查询，该桥梁通过语言解析与规范化自动推导出紧凑的规范主体标签集合，进而利用文本条件化的开放词汇分割将标签映射为查询条件化的实例掩码。该桥梁还将轻量级语义实例标记与持久帧索引嵌入每一帧，有效将长距离时间推理转化为Vid-LLMs的显式视觉线索。MarkIt{}采用推理即用的即插即用设计，无需修改Vid-LLM权重，且完全兼容监督微调。在多个主流时刻检索与高光检测基准上的实验表明，MarkIt{}取得了最先进的结果，并在广泛现有模型中实现一致的时间定位性能提升。