71 citations · 225 across the 30 of their papers we have counts for
31 papers
Long-Term Dynamic Window Approach for Kinodynamic Local Planning in Static and Crowd Environments
Zhiqiang Jian, Songyi Zhang, Lingfeng Sun +3
Local planning for a differential wheeled robot is designed to generate kinodynamic feasible actions that guide the robot to a goal position along the navigation path while avoidin…
Quadric Representations for LiDAR Odometry, Mapping and Localization
Chao Xia, Chenfeng Xu, Patrick Rim +5
Current LiDAR odometry, mapping and localization methods leverage point-wise representations of 3D scenes and achieve high accuracy in autonomous driving tasks. However, the space-…
Tightly Coupled Learning Strategy for Weakly Supervised Hierarchical Place Recognition
Y. Shen, R. Wang, W. Zuo +1
Visual place recognition (VPR) is a key issue for robotics and autonomous systems. For the trade-off between time and performance, most of methods use the coarse-to-fine hierarchic…
LiVLR: A Lightweight Visual-Linguistic Reasoning Framework for Video Question Answering
Jingjing Jiang, Ziyi Liu, Nanning Zheng
Video Question Answering (VideoQA), aiming to correctly answer the given question based on understanding multi-modal video content, is challenging due to the rich video content. Fr…
Instance-Conditional Knowledge Distillation for Object Detection
Zijian Kang, Peizhen Zhang, Xiangyu Zhang +2
Knowledge distillation has shown great success in classification, however, it is still challenging for detection. In a typical image for detection, representations from different l…
LGD: Label-guided Self-distillation for Object Detection
Peizhen Zhang, Zijian Kang, Tong Yang +3
In this paper, we propose the first self-distillation framework for general object detection, termed LGD (Label-Guided self-Distillation). Previous studies rely on a strong pretrai…
Model-based Decision Making with Imagination for Autonomous Parking
Ziyue Feng, Yu Chen, Shitao Chen +1
Autonomous parking technology is a key concept within autonomous driving research. This paper will propose an imaginative autonomous parking algorithm to solve issues concerned wit…
Enriching Local and Global Contexts for Temporal Action Localization
Zixin Zhu, Wei Tang, Le Wang +2
Effectively tackling the problem of temporal action localization (TAL) necessitates a visual representation that jointly pursues two confounding goals, i.e., fine-grained discrimin…
Unlimited Neighborhood Interaction for Heterogeneous Trajectory Prediction
Fang Zheng, Le Wang, Sanping Zhou +4
Understanding complex social interactions among agents is a key challenge for trajectory prediction. Most existing methods consider the interactions between pairwise traffic agents…
X-GGM: Graph Generative Modeling for Out-of-Distribution Generalization in Visual Question Answering
Jingjing Jiang, Ziyi Liu, Yifan Liu +2
Encouraging progress has been made towards Visual Question Answering (VQA) in recent years, but it is still challenging to enable VQA models to adaptively generalize to out-of-dist…
Adversarial Attack and Defense in Deep Ranking
Mo Zhou, Le Wang, Zhenxing Niu +3
Deep Neural Network classifiers are vulnerable to adversarial attack, where an imperceptible perturbation could result in misclassification. However, the vulnerability of DNN-based…
Video Imprint
Zhanning Gao, Le Wang, Nebojsa Jojic +3
A new unified video analytics framework (ER3) is proposed for complex event retrieval, recognition and recounting, based on the proposed video imprint representation, which exploit…
Weakly Supervised Temporal Action Localization Through Learning Explicit Subspaces for Action and Context
Ziyi Liu, Le Wang, Wei Tang +3
Weakly-supervised Temporal Action Localization (WS-TAL) methods learn to localize temporal starts and ends of action instances in a video under only video-level supervision. Existi…
ACSNet: Action-Context Separation Network for Weakly Supervised Temporal Action Localization
Ziyi Liu, Le Wang, Qilin Zhang +4
The object of Weakly-supervised Temporal Action Localization (WS-TAL) is to localize all action instances in an untrimmed video with only video-level supervision. Due to the lack o…
Practical Relative Order Attack in Deep Ranking
Mo Zhou, Le Wang, Zhenxing Niu +4
Recent studies unveil the vulnerabilities of deep ranking models, where an imperceptible perturbation can trigger dramatic changes in the ranking result. While previous attempts fo…
Fine-Grained Dynamic Head for Object Detection
Lin Song, Yanwei Li, Zhengkai Jiang +4
The Feature Pyramid Network (FPN) presents a remarkable approach to alleviate the scale variance in object representation by performing instance-level assignments. Nevertheless, th…
Rethinking Learnable Tree Filter for Generic Feature Transform
Lin Song, Yanwei Li, Zhengkai Jiang +5
The Learnable Tree Filter presents a remarkable approach to model structure-preserving relations for semantic segmentation. Nevertheless, the intrinsic geometric constraint forces…
End-to-End Object Detection with Fully Convolutional Network
Jianfeng Wang, Lin Song, Zeming Li +3
Mainstream object detectors based on the fully convolutional network has achieved impressive performance. While most of them still need a hand-designed non-maximum suppression (NMS…
Multi-agent Policy Optimization with Approximatively Synchronous Advantage Estimation
Lipeng Wan, Xuwei Song, Xuguang Lan +1
Cooperative multi-agent tasks require agents to deduce their own contributions with shared global rewards, known as the challenge of credit assignment. General methods for policy b…
Learning to Infer Unseen Single-/Multi-Attribute-Object Compositions with Graph Networks
Hui Chen, Jingjing Jiang, Nanning Zheng
Inferring the unseen attribute-object composition is critical to make machines learn to decompose and compose complex concepts like people. Most existing methods are limited to the…
Discriminative Feature Learning with Foreground Attention for Person Re-Identification
Sanping Zhou, Jinjun Wang, Deyu Meng +3
The performance of person re-identification (Re-ID) has been seriously effected by the large cross-view appearance variations caused by mutual occlusions and background clutters. H…
Attention-based Temporal Weighted Convolutional Neural Network for Action Recognition
Jinliang Zang, Le Wang, Ziyi Liu +4
Research in human action recognition has accelerated significantly since the introduction of powerful machine learning tools such as Convolutional Neural Networks (CNNs). However,…
Feature Selective Small Object Detection via Knowledge-based Recurrent Attentive Neural Network
Kai Yi, Zhiqiang Jian, Shitao Chen +1
At present, the performance of deep neural network in general object detection is comparable to or even surpasses that of human beings. However, due to the limitations of deep lear…
Deep Self-Paced Learning for Person Re-Identification
Sanping Zhou, Jinjun Wang, Deyu Meng +4
Person re-identification (Re-ID) usually suffers from noisy samples with background clutter and mutual occlusion, which makes it extremely difficult to distinguish different indivi…