SECOND: Sparsely Embedded Convolutional Detection
LiDAR-based or RGB-D-based object detection is used in numerous applications, ranging from autonomous driving to robot vision. Voxel-based 3D convolutional networks have been us...
Publications
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1,119 publications
Trust Region Methods
Preface 1. Introduction Part I. Preliminaries: 2. Basic Concepts 3. Basic Analysis and Optimality Conditions 4. Basic Linear Algebra 5. Krylov Subspace Methods Part II. Trust-Re...
Microscopic Traffic Simulation using SUMO
Microscopic traffic simulation is an invaluable tool for traffic research. In recent years, both the scope of research and the capabilities of the tools have been extended consi...
High Performance Visual Tracking with Siamese Region Proposal Network
Visual object tracking has been a fundamental topic in recent years and many deep learning based trackers have achieved state-of-the-art performance on multiple benchmarks. Howe...
Restormer: Efficient Transformer for High-Resolution Image Restoration
Since convolutional neural networks (CNNs) perform well at learning generalizable image priors from large-scale data, these models have been extensively applied to image restora...
State-of-the-art in artificial neural network applications: A survey
This is a survey of neural network applications in the real-world scenario. It provides a taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of ...
Trust in Organizations: Frontiers of Theory and Research
Whither Trust? - Tom R Tyler and Roderick M Kramer Trust in Organizations - W E Douglas Creed and Raymond E Miles A Conceptual Framework Linking Organizational Forms, Managerial...
DOTA: A Large-Scale Dataset for Object Detection in Aerial Images
Object detection is an important and challenging problem in computer vision. Although the past decade has witnessed major advances in object detection in natural scenes, such su...
SciBERT: A Pretrained Language Model for Scientific Text
Iz Beltagy, Kyle Lo, Arman Cohan. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural La...
PointRCNN: 3D Object Proposal Generation and Detection From Point Cloud
In this paper, we propose PointRCNN for 3D object detection from raw point cloud. The whole framework is composed of two stages: stage-1 for the bottom-up 3D proposal generation...
Selective Kernel Networks
In standard Convolutional Neural Networks (CNNs), the receptive fields of artificial neurons in each layer are designed to share the same size. It is well-known in the neuroscie...
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting
Timely accurate traffic forecast is crucial for urban traffic control and guidance. Due to the high nonlinearity and complexity of traffic flow, traditional methods cannot satis...