2023年8月1日 · In this article, we develop a G-S information enhanced lightweight VO (GSL-VO) that can work particularly well in dynamic environments. Specifically, on the one hand, to improve the robustness of VO through G-S information, we first come up with a novel image enhancement module to tackle motion blur, thus enabling accurate geometric and ...

2021年4月25日 · ggseg 是2018年出的R工具包，可以在R中绘制到皮层或者皮层下区域的统计结果。 和brainconn一样，解决了需要从R导出数据用其他 软件 作图的问题。 ggseg基于 ggplot，因此能用ggplot的方式调整作图效果，比如facet_wrap和theme，同时还兼容了dplyr的管道命令 (%>%)。 在最近1.6的版本中做出了很多主要的更新，引入了geom_brain/geom_sf，更符合ggplot的规范，让作图的逻辑更加清晰。 之前使用的 ggseg () 的作图方式仍然会保留一段时 …

Currently, 7 projects are organized for SemanticKITTI dataset: The repository consists of C++ and ROS. But, for python users, we also provide all the previously extracted ground label files. Please check the explanations below. If our open sources have been helpful, please cite the below papers published by our research group:

gSeg: Graph-Based Change-Point Detection (g-Segmentation) Using an approach based on similarity graph to estimate change-point(s) and the corresponding p-values. Can be applied to any type of data (high-dimensional, non-Euclidean, etc.) as long as a reasonable similarity measure is available.

This is the implementation of Generalized Few-shot Semantic Segmentation (CVPR 2022). Different from PFENet (5953 images), in GFS-Seg, the training set of Pascal-VOC is used with augmented data (10582 images), following the original PSPNet, as done in most of works in normal semantic segmentation.

2025年3月3日 · For sequence with no repeated observations, if you believe the sequence has at most one change point, the function gseg1 should be used; if you believe an interval of the sequence has a changed distribution, the function gseg2 should be used. If you feel the sequence has multiple change-points, you can use gseg1 and gseg2 multiple times.

We present good feature matching, an active map-to-frame feature matching method. Feature matching effort is tied to submatrix selection, which has combinatorial time complexity and requires choosing a scoring metric. Via simulation, the Max-logDet matrix revealing metric is shown to perform best.

2020年10月23日 · This package can be used to estimate change-points in a sequence of observations, where the observation can be a vector or a data object, e.g., a network. A similarity graph is required. It can be a minimum spanning tree, a minimum distance pairing, a nearest neighbor graph, or a graph based on domain knowledge.

2024年11月26日 · In this paper, the graph segmentation (GSeg) method has been proposed. This solution is a novel graph neural network framework for network embedding that leverages the inherent characteristics of nodes and the underlying local network topology. The key innovation of GSeg lies in its encoder-decoder …

2020年10月23日 · gSeg: Graph-Based Change-Point Detection (g-Segmentation) Using an approach based on similarity graph to estimate change-point(s) and the corresponding p-values. Can be applied to any type of data (high-dimensional, non-Euclidean, etc.) as long as a reasonable similarity measure is available.