Field of Junctions: Extracting Boundary Structure at Low SNR

3D 立体接点场：一种噪声鲁棒、无需训练的结构先验用于体积分量逆问题

3D Field of Junctions: A Noise-Robust, Training-Free Structural Prior for Volumetric Inverse Problems

本文提出3D FoJ方法，通过优化3D楔形接点来实现体积分量逆问题的去噪，无需训练数据，保留和增强3D边缘和角结构，适用于低信噪比下的多种3D成像任务。

Learning to Parse Wireframes in Images of Man-Made Environments

In this paper, we propose a learning-based approach to the task of automatically extracting a "wireframe" representation for images of cluttered man-made environments. The wireframe (see Fig. 1) contains all salient straight lines and their junctions of the scene that encode efficiently and accurately large-scale geometry and object shapes. To this end, we have built a very large new dataset of over 5,000 images with wireframes thoroughly labelled by humans. We have proposed two convolutional neural networks that are suitable for extracting junctions and lines with large spatial support, respe…

边界注意力：学习曲线、角点、连接点与分组

Boundary Attention: Learning curves, corners, junctions and grouping

该研究提出一种带边界注意力机制的轻量级自底向上网络，可学习局部边界结构与尺度一致性，生成丰富的非栅格化边界表示，能在合成形状训练后泛化至低光照噪声图像的边界提取任务。

GeoSay: A Geometric Saliency for Extracting Buildings in Remote Sensing Images

Automatic extraction of buildings in remote sensing images is an important but challenging task and finds many applications in different fields such as urban planning, navigation and so on. This paper addresses the problem of buildings extraction in very high-spatial-resolution (VHSR) remote sensing (RS) images, whose spatial resolution is often up to half meters and provides rich information about buildings. Based on the observation that buildings in VHSR-RS images are always more distinguishable in geometry than in texture or spectral domain, this paper proposes a geometric building index (G…

Instance Segmentation Based Graph Extraction for Handwritten Circuit Diagram Images

Handwritten circuit diagrams from educational scenarios or historic sources usually exist on analogue media. For deriving their functional principles or flaws automatically, they need to be digitized, extracting their electrical graph. Recently, the base technologies for automated pipelines facilitating this process shifted from computer vision to machine learning. This paper describes an approach for extracting both the electrical components (including their terminals and describing texts) as well their interconnections (including junctions and wire hops) by the means of instance segmentation…

迈向鲁棒的基于事件引导的低光图像增强：一个大规模真实世界事件-图像数据集与新方法

Towards Robust Event-guided Low-Light Image Enhancement: A Large-Scale Real-World Event-Image Dataset and Novel Approach

本文针对事件引导低光图像增强缺乏真实世界时空对齐数据的问题，构建了超30K对室内外事件-图像数据集，并提出EvLight方法，通过多尺度融合和SNR引导区域特征选择实现鲁棒增强，性能显著优于帧方法。