536 research outputs found
Unified Chinese License Plate Detection and Recognition with High Efficiency
Recently, deep learning-based methods have reached an excellent performance
on License Plate (LP) detection and recognition tasks. However, it is still
challenging to build a robust model for Chinese LPs since there are not enough
large and representative datasets. In this work, we propose a new dataset named
Chinese Road Plate Dataset (CRPD) that contains multi-objective Chinese LP
images as a supplement to the existing public benchmarks. The images are mainly
captured with electronic monitoring systems with detailed annotations. To our
knowledge, CRPD is the largest public multi-objective Chinese LP dataset with
annotations of vertices. With CRPD, a unified detection and recognition network
with high efficiency is presented as the baseline. The network is end-to-end
trainable with totally real-time inference efficiency (30 fps with 640p). The
experiments on several public benchmarks demonstrate that our method has
reached competitive performance. The code and dataset will be publicly
available at https://github.com/yxgong0/CRPD
LiDAR-Camera Panoptic Segmentation via Geometry-Consistent and Semantic-Aware Alignment
3D panoptic segmentation is a challenging perception task that requires both
semantic segmentation and instance segmentation. In this task, we notice that
images could provide rich texture, color, and discriminative information, which
can complement LiDAR data for evident performance improvement, but their fusion
remains a challenging problem. To this end, we propose LCPS, the first
LiDAR-Camera Panoptic Segmentation network. In our approach, we conduct
LiDAR-Camera fusion in three stages: 1) an Asynchronous Compensation Pixel
Alignment (ACPA) module that calibrates the coordinate misalignment caused by
asynchronous problems between sensors; 2) a Semantic-Aware Region Alignment
(SARA) module that extends the one-to-one point-pixel mapping to one-to-many
semantic relations; 3) a Point-to-Voxel feature Propagation (PVP) module that
integrates both geometric and semantic fusion information for the entire point
cloud. Our fusion strategy improves about 6.9% PQ performance over the
LiDAR-only baseline on NuScenes dataset. Extensive quantitative and qualitative
experiments further demonstrate the effectiveness of our novel framework. The
code will be released at https://github.com/zhangzw12319/lcps.git.Comment: Accepted as ICCV 2023 pape
Experimental Study on Wind Erosion of Concrete Building Surface in Wind-Sand Environment
In this paper, the effects of different wind-sand attack angle, wind speed, action time, concrete strength, sand particle size, and sand content on the surface wind erosion of concrete structures are experimentally studied. Wind erosion rate and strength loss rate are defined as the indexes to measure the degree of wind erosion of concrete. According to the similarity theory, the actual situation is deduced based on the wind erosion test, and the wind erosion time corresponding to the wind speed, the action time of wind sand, and the simulation test in the case of sand content is obtained. it makes the experimental study of wind erosion on concrete buildings to have more practical significance
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