QSCP：超越类名提示的查询引导语义变化解析
QSCP: Beyond Class-Name Prompts for Query-Guided Semantic Change Parsing
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中文总结 AI 辅助
提出QSCP方法，通过解析查询意图与语义槽，结合双向视觉证据，实现查询引导的语义变化解析，支持类别、同义词及句子查询，优于现有基线。
中文摘要 AI 辅助
传统变化检测（CD）识别双时相遥感图像之间的变化，而语义变化检测（SCD）则分配预定义的土地覆盖类别。然而，映射所有变化可能无法满足用户的特定需求。引用变化检测（RCD）通过类别提示实现选择性检索。然而，现有的基于类别提示的RCD使用查询类别来指定变化的目标，仅返回相应区域的二值掩码。用户可能反而请求特定的转变和配对的语义图，以理解什么变成了什么。此类请求需要显式的源和目标推理，而不仅仅是目标类别定位。为满足这些需求，我们提出了查询引导语义变化解析（QSCP），它支持类别名称、同义词和携带意图的句子，并返回查询特定的掩码及配对的时序语义图。QSCP将请求解析为意图和语义槽，组合双向视觉证据，并通过查询条件解码器预测两个时序状态。在SECOND数据集上，QSCP在同义词、句子和转变查询上优于RCDNet，并在端到端语义预测方面优于所评估的语义基线。WHU-CDC实验进一步评估了跨数据集迁移以及无需目标域训练时等价表达的一致性。代码可在以下https URL获取。
英文摘要
Traditional change detection (CD) identifies changes between bi-temporal remote sensing images, while semantic change detection (SCD) assigns predefined land-cover classes. However, mapping all changes may not meet a user's specific needs. Referring change detection (RCD) enables selective retrieval through category prompts. However, existing category-prompted RCD uses the queried category to specify the destination of a change and returns only a binary mask of the corresponding regions. Users may instead request a particular transition and paired semantic maps to understand what changed into what. Such requests require explicit source and target reasoning beyond target-class localization. To address these needs, we propose query-guided semantic change parsing (QSCP), which supports category names, synonyms, and intent-bearing sentences and returns a query-specific mask with paired temporal semantic maps. QSCP parses requests into intents and semantic slots, composes bidirectional visual evidence, and predicts both temporal states with a query-conditioned decoder. On SECOND, QSCP outperforms RCDNet on synonym, sentence, and transition queries and improves end-to-end semantic prediction over evaluated semantic baselines. WHU-CDC experiments further assess cross-dataset transfer and consistency across equivalent expressions without target-domain training. Code is available at https://github.com/qianyuancs/QSCP
