论文标题
3DRM：3D对象检测的配对关系模块
3DRM:Pair-wise relation module for 3D object detection
论文作者
论文摘要
事实证明，上下文是3D场景理解的对象布局推理中最重要的因素之一。现有的深层上下文模型要么学习上下文编码的整体特征，要么依靠预定义的场景模板进行上下文建模。我们认为，场景从对象关系推理中理解好处，这能够减轻3D对象检测的歧义，从而有助于更准确，稳健地定位和分类3D对象。为了实现这一目标，我们提出了一个新颖的3D关系模块（3DRM），该模块的原因是在成对级别上。 3DRM预测对象之间的语义和空间关系，并提取对象关系特征。我们分别将3DRM插入基于建议的3D对象检测管道中来证明3DRM的效果。广泛的评估表明3DM对3D对象检测的有效性和概括。我们的源代码可从https://github.com/lanlan96/3drm获得。
Context has proven to be one of the most important factors in object layout reasoning for 3D scene understanding. Existing deep contextual models either learn holistic features for context encoding or rely on pre-defined scene templates for context modeling. We argue that scene understanding benefits from object relation reasoning, which is capable of mitigating the ambiguity of 3D object detections and thus helps locate and classify the 3D objects more accurately and robustly. To achieve this, we propose a novel 3D relation module (3DRM) which reasons about object relations at pair-wise levels. The 3DRM predicts the semantic and spatial relationships between objects and extracts the object-wise relation features. We demonstrate the effects of 3DRM by plugging it into proposal-based and voting-based 3D object detection pipelines, respectively. Extensive evaluations show the effectiveness and generalization of 3DRM on 3D object detection. Our source code is available at https://github.com/lanlan96/3DRM.
