58 citations · 111 across the 21 of their papers we have counts for
22 papers
i-Octree: A Fast, Lightweight, and Dynamic Octree for Proximity Search
Jun Zhu, Hongyi Li, Zhepeng Wang +2
Establishing the correspondences between newly acquired points and historically accumulated data (i.e., map) through nearest neighbors search is crucial in numerous robotic applica…
A Positive-Unlabeled Metric Learning Framework for Document-Level Relation Extraction with Incomplete Labeling
Ye Wang, Huazheng Pan, Tao Zhang +2
The goal of document-level relation extraction (RE) is to identify relations between entities that span multiple sentences. Recently, incomplete labeling in document-level RE has r…
Three-way causal attribute partial order structure analysis
Xue Zaifa, Lu Huibin, Zhang Tao +2
As an emerging concept cognitive learning model, partial order formal structure analysis (POFSA) has been widely used in the field of knowledge processing. In this paper, we propos…
Efficient Exploration Using Extra Safety Budget in Constrained Policy Optimization
Haotian Xu, Shengjie Wang, Zhaolei Wang +4
Reinforcement learning (RL) has achieved promising results on most robotic control tasks. Safety of learning-based controllers is an essential notion of ensuring the effectiveness…
Adversarial Attack with Raindrops
Jiyuan Liu, Bingyi Lu, Mingkang Xiong +2
Deep neural networks (DNNs) are known to be vulnerable to adversarial examples, which are usually designed artificially to fool DNNs, but rarely exist in real-world scenarios. In t…
Graph Analysis in Decentralized Online Social Networks with Fine-Grained Privacy Protection
Lele Zheng, Bowen Deng, Tao Zhang +2
Graph analysts cannot directly obtain the global structure in decentralized social networks, and analyzing such a network requires collecting local views of the social graph from i…
BuildMapper: A Fully Learnable Framework for Vectorized Building Contour Extraction
Shiqing Wei, Tao Zhang, Shunping Ji +2
Deep learning based methods have significantly boosted the study of automatic building extraction from remote sensing images. However, delineating vectorized and regular building c…
Deep Smart Contract Intent Detection
Youwei Huang, Sen Fang, Jianwen Li +3
In recent years, research in software security has concentrated on identifying vulnerabilities in smart contracts to prevent significant losses of crypto assets on blockchains. Des…
A Unified Positive-Unlabeled Learning Framework for Document-Level Relation Extraction with Different Levels of Labeling
Ye Wang, Xinxin Liu, Wenxin Hu +1
Document-level relation extraction (RE) aims to identify relations between entities across multiple sentences. Most previous methods focused on document-level RE under full supervi…
InfoAT: Improving Adversarial Training Using the Information Bottleneck Principle
Mengting Xu, Tao Zhang, Zhongnian Li +1
Adversarial training (AT) has shown excellent high performance in defending against adversarial examples. Recent studies demonstrate that examples are not equally important to the…
CREAM: Weakly Supervised Object Localization via Class RE-Activation Mapping
Jilan Xu, Junlin Hou, Yuejie Zhang +5
Weakly Supervised Object Localization (WSOL) aims to localize objects with image-level supervision. Existing works mainly rely on Class Activation Mapping (CAM) derived from a clas…
Scale-Invariant Adversarial Attack for Evaluating and Enhancing Adversarial Defenses
Mengting Xu, Tao Zhang, Zhongnian Li +1
Efficient and effective attacks are crucial for reliable evaluation of defenses, and also for developing robust models. Projected Gradient Descent (PGD) attack has been demonstrate…
M3D-VTON: A Monocular-to-3D Virtual Try-On Network
Fuwei Zhao, Zhenyu Xie, Michael Kampffmeyer +5
Virtual 3D try-on can provide an intuitive and realistic view for online shopping and has a huge potential commercial value. However, existing 3D virtual try-on methods mainly rely…
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack
Mengting Xu, Tao Zhang, Zhongnian Li +2
Deep learning models (with neural networks) have been widely used in challenging tasks such as computer-aided disease diagnosis based on medical images. Recent studies have shown d…
Generative Partial Visual-Tactile Fused Object Clustering
Tao Zhang, Yang Cong, Gan Sun +3
Visual-tactile fused sensing for object clustering has achieved significant progresses recently, since the involvement of tactile modality can effectively improve clustering perfor…
Re-weighting and 1-Point RANSAC-Based PnP Solution to Handle Outliers
Haoyin Zhou, Tao Zhang, Jagadeesan Jayender
The ability to handle outliers is essential for performing the perspective-n-point (PnP) approach in practical applications, but conventional RANSAC+P3P or P4P methods have high ti…
Differentially Private Collaborative Intrusion Detection Systems For VANETs
Tao Zhang, Quanyan Zhu
Vehicular ad hoc network (VANET) is an enabling technology in modern transportation systems for providing safety and valuable information, and yet vulnerable to a number of attacks…
MZET: Memory Augmented Zero-Shot Fine-grained Named Entity Typing
Tao Zhang, Congying Xia, Chun-Ta Lu +1
Named entity typing (NET) is a classification task of assigning an entity mention in the context with given semantic types. However, with the growing size and granularity of the en…
Adaptive Trajectory Estimation with Power Limited Steering Model under Perturbation Compensation
Weipeng Li, Xiaogang Yang, Ruitao Lu +3
Trajectory estimation of maneuvering objects is applied in numerous tasks like navigation, path planning and visual tracking. Many previous works get impressive results in the stri…
Visual Tactile Fusion Object Clustering
Tao Zhang, Yang Cong, Gan Sun +2
Object clustering, aiming at grouping similar objects into one cluster with an unsupervised strategy, has been extensivelystudied among various data-driven applications. However, m…
A Penalized Inequality-Constrained Approach for Robust Beamforming with DoF Limitation
Wenqiang Pu, Jinjun Xiao, Tao Zhang +1
A well-known challenge in beamforming is how to optimally utilize the degrees of freedom (DoF) of the array to design a robust beamformer, especially when the array DoF is limited.…
ARMIN: Towards a More Efficient and Light-weight Recurrent Memory Network
Zhangheng Li, Jia-Xing Zhong, Jingjia Huang +3
In recent years, memory-augmented neural networks(MANNs) have shown promising power to enhance the memory ability of neural networks for sequential processing tasks. However, previ…