82 citations · 206 across the 32 of their papers we have counts for
11 papers · 1 filter
Aerial Height Prediction and Refinement Neural Networks with Semantic and Geometric Guidance
Elhousni Mahdi, Zhang Ziming, Huang Xinming
Deep learning provides a powerful new approach to many computer vision tasks. Height prediction from aerial images is one of those tasks that benefited greatly from the deployment…
Self-supervised Geometric Features Discovery via Interpretable Attention for Vehicle Re-Identification and Beyond
Ming Li, Xinming Huang, Ziming Zhang
To learn distinguishable patterns, most of recent works in vehicle re-identification (ReID) struggled to redevelop official benchmarks to provide various supervisions, which requir…
TreeRNN: Topology-Preserving Deep GraphEmbedding and Learning
Yecheng Lyu, Ming Li, Xinming Huang +3
General graphs are difficult for learning due to their irregular structures. Existing works employ message passing along graph edges to extract local patterns using customized grap…
DepthNet: Real-Time LiDAR Point Cloud Depth Completion for Autonomous Vehicles
Lin Bai, Yiming Zhao, Mahdi Elhousni +1
Autonomous vehicles rely heavily on sensors such as camera and LiDAR, which provide real-time information about their surroundings for the tasks of perception, planning and control…
RoadNet-RT: High Throughput CNN Architecture and SoC Design for Real-Time Road Segmentation
Lin Bai, Yecheng Lyu, Xinming Huang
In recent years, convolutional neural network has gained popularity in many engineering applications especially for computer vision. In order to achieve better performance, often m…
A Survey on 3D LiDAR Localization for Autonomous Vehicles
Mahdi Elhousni, Xinming Huang
LiDAR sensors are becoming one of the most essential sensors in achieving full autonomy for self driving cars. LiDARs are able to produce rich, dense and precise spatial data, whic…
Automatic Building and Labeling of HD Maps with Deep Learning
Mahdi Elhousni, Yecheng Lyu, Ziming Zhang +1
In a world where autonomous driving cars are becoming increasingly more common, creating an adequate infrastructure for this new technology is essential. This includes building and…
Pedestrian Tracking with Gated Recurrent Units and Attention Mechanisms
Mahdi Elhousni, Xinming Huang
Pedestrian tracking has long been considered an important problem, especially in security applications. Previously,many approaches have been proposed with various types of sensors.…
A Unified Hardware Architecture for Convolutions and Deconvolutions in CNN
Lin Bai, Yecheng Lyu, Xinming Huang
In this paper, a scalable neural network hardware architecture for image segmentation is proposed. By sharing the same computing resources, both convolution and deconvolution opera…
PointNet on FPGA for Real-Time LiDAR Point Cloud Processing
Lin Bai, Yecheng Lyu, Xin Xu +1
LiDAR sensors have been widely used in many autonomous vehicle modalities, such as perception, mapping, and localization. This paper presents an FPGA-based deep learning platform f…
Learning to Segment 3D Point Clouds in 2D Image Space
Yecheng Lyu, Xinming Huang, Ziming Zhang
In contrast to the literature where local patterns in 3D point clouds are captured by customized convolutional operators, in this paper we study the problem of how to effectively a…