Scholarlink

<p>Image stitching often faces challenges due to varying capture angles, positional differences, and object movements, leading to misalignments and visual discrepancies. Traditional seam carving methods neglect semantic information, causing disruptions in foreground continuity. We introduce SemanticStitch, a deep learning-based framework that incorporates semantic priors of foreground objects to preserve their integrity and enhance visual coherence. Our approach includes a novel loss function that emphasizes the semantic integrity of salient objects, significantly improving stitching quality. We also present two specialized real-world datasets to evaluate our method’s effectiveness. Experimental results demonstrate substantial improvements over traditional techniques, providing robust support for practical applications. The codes are available at <a href="https://github.com/Pokerman8/OAIV-Coherence">https://github.com/Pokerman8/OAIV-Coherence</a>.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

SemanticStitch: enhancing image coherence through foreground-aware seam carving

  • 期刊论文

  • 发表日期：

    2025年12月15日

查看全文
  • Ji-Ping Jin,
  • Chen-Bin Feng,
  • Rui Fan,
  • Chi-Man Vong

摘要

Image stitching often faces challenges due to varying capture angles, positional differences, and object movements, leading to misalignments and visual discrepancies. Traditional seam carving methods neglect semantic information, causing disruptions in foreground continuity. We introduce SemanticStitch, a deep learning-based framework that incorporates semantic priors of foreground objects to preserve their integrity and enhance visual coherence. Our approach includes a novel loss function that emphasizes the semantic integrity of salient objects, significantly improving stitching quality. We also present two specialized real-world datasets to evaluate our method’s effectiveness. Experimental results demonstrate substantial improvements over traditional techniques, providing robust support for practical applications. The codes are available at https://github.com/Pokerman8/OAIV-Coherence.