780 citations · 1.8k across the 45 of their papers we have counts for
46 papers
InteractionNet: Joint Planning and Prediction for Autonomous Driving with Transformers
Jiawei Fu, Yanqing Shen, Zhiqiang Jian +3
Planning and prediction are two important modules of autonomous driving and have experienced tremendous advancement recently. Nevertheless, most existing methods regard planning an…
Complementing Onboard Sensors with Satellite Map: A New Perspective for HD Map Construction
Wenjie Gao, Jiawei Fu, Yanqing Shen +3
High-definition (HD) maps play a crucial role in autonomous driving systems. Recent methods have attempted to construct HD maps in real-time using vehicle onboard sensors. Due to t…
FS-Depth: Focal-and-Scale Depth Estimation from a Single Image in Unseen Indoor Scene
Chengrui Wei, Meng Yang, Lei He +1
It has long been an ill-posed problem to predict absolute depth maps from single images in real (unseen) indoor scenes. We observe that it is essentially due to not only the scale-…
CoBigICP: Robust and Precise Point Set Registration using Correntropy Metrics and Bidirectional Correspondence
Pengyu Yin, Di Wang, Shaoyi Du +3
In this paper, we propose a novel probabilistic variant of iterative closest point (ICP) dubbed as CoBigICP. The method leverages both local geometrical information and global nois…
Using Detection, Tracking and Prediction in Visual SLAM to Achieve Real-time Semantic Mapping of Dynamic Scenarios
Xingyu Chen, Jianru Xue, Jianwu Fang +2
In this paper, we propose a lightweight system, RDS-SLAM, based on ORB-SLAM2, which can accurately estimate poses and build semantic maps at object level for dynamic scenarios in r…
Trajectory Forecasting from Detection with Uncertainty-Aware Motion Encoding
Pu Zhang, Lei Bai, Jianru Xue +3
Trajectory forecasting is critical for autonomous platforms to make safe planning and actions. Currently, most trajectory forecasting methods assume that object trajectories have b…
Multi-Scale Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition
Pengfei Zhang, Cuiling Lan, Wenjun Zeng +3
Skeleton data is of low dimension. However, there is a trend of using very deep and complicated feedforward neural networks to model the skeleton sequence without considering the c…
INVIGORATE: Interactive Visual Grounding and Grasping in Clutter
Hanbo Zhang, Yunfan Lu, Cunjun Yu +3
This paper presents INVIGORATE, a robot system that interacts with human through natural language and grasps a specified object in clutter. The objects may occlude, obstruct, or ev…
Probabilistic Human Motion Prediction via A Bayesian Neural Network
Jie Xu, Xingyu Chen, Xuguang Lan +1
Human motion prediction is an important and challenging topic that has promising prospects in efficient and safe human-robot-interaction systems. Currently, the majority of the hum…
REGRAD: A Large-Scale Relational Grasp Dataset for Safe and Object-Specific Robotic Grasping in Clutter
Hanbo Zhang, Deyu Yang, Han Wang +4
Despite the impressive progress achieved in robotic grasping, robots are not skilled in sophisticated tasks (e.g. search and grasp a specified target in clutter). Such tasks involv…
A Driving Behavior Recognition Model with Bi-LSTM and Multi-Scale CNN
He Zhang, Zhixiong Nan, Tao Yang +2
In autonomous driving, perceiving the driving behaviors of surrounding agents is important for the ego-vehicle to make a reasonable decision. In this paper, we propose a neural net…
Conditional Uncorrelation and Efficient Non-approximate Subset Selection in Sparse Regression
Jianji Wang, Qi Liu, Shupei Zhang +2
Given -dimensional responsors and -dimensional predictors, sparse regression finds at most predictors for each responsor for linear approximation, $1\leq k \leq d…
A Boundary Based Out-of-Distribution Classifier for Generalized Zero-Shot Learning
Xingyu Chen, Xuguang Lan, Fuchun Sun +1
Generalized Zero-Shot Learning (GZSL) is a challenging topic that has promising prospects in many realistic scenarios. Using a gating mechanism that discriminates the unseen sample…
Traffic Agent Trajectory Prediction Using Social Convolution and Attention Mechanism
Tao Yang, Zhixiong Nan, He Zhang +2
The trajectory prediction is significant for the decision-making of autonomous driving vehicles. In this paper, we propose a model to predict the trajectories of target agents arou…
REGNet: REgion-based Grasp Network for End-to-end Grasp Detection in Point Clouds
Binglei Zhao, Hanbo Zhang, Xuguang Lan +3
Reliable robotic grasping in unstructured environments is a crucial but challenging task. The main problem is to generate the optimal grasp of novel objects from partial noisy obse…
Visual Semantic SLAM with Landmarks for Large-Scale Outdoor Environment
Zirui Zhao, Yijun Mao, Yan Ding +2
Semantic SLAM is an important field in autonomous driving and intelligent agents, which can enable robots to achieve high-level navigation tasks, obtain simple cognition or reasoni…
Learnable Tree Filter for Structure-preserving Feature Transform
Lin Song, Yanwei Li, Zeming Li +4
Learning discriminative global features plays a vital role in semantic segmentation. And most of the existing methods adopt stacks of local convolutions or non-local blocks to capt…
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks
Pengfei Zhang, Jianru Xue, Cuiling Lan +3
Recurrent neural networks (RNNs) are capable of modeling temporal dependencies of complex sequential data. In general, current available structures of RNNs tend to concentrate on c…
An encoding framework with brain inner state for natural image identification
Hao Wu, Ziyu Zhu, Jiayi Wang +2
Neural encoding and decoding, which aim to characterize the relationship between stimuli and brain activities, have emerged as an important area in cognitive neuroscience. Traditio…
Hindsight Trust Region Policy Optimization
Hanbo Zhang, Site Bai, Xuguang Lan +2
Reinforcement Learning(RL) with sparse rewards is a major challenge. We propose \emph{Hindsight Trust Region Policy Optimization}(HTRPO), a new RL algorithm that extends the highly…
Minimum Error Entropy Kalman Filter
Badong Chen, Lujuan Dang, Yuantao Gu +2
To date most linear and nonlinear Kalman filters (KFs) have been developed under the Gaussian assumption and the well-known minimum mean square error (MMSE) criterion. In order to…
Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition
Pengfei Zhang, Cuiling Lan, Wenjun Zeng +3
Skeleton-based human action recognition has attracted great interest thanks to the easy accessibility of the human skeleton data. Recently, there is a trend of using very deep feed…
SR-LSTM: State Refinement for LSTM towards Pedestrian Trajectory Prediction
Pu Zhang, Wanli Ouyang, Pengfei Zhang +2
In crowd scenarios, reliable trajectory prediction of pedestrians requires insightful understanding of their social behaviors. These behaviors have been well investigated by plenty…
Consistency-aware Shading Orders Selective Fusion for Intrinsic Image Decomposition
Yuanliu Liu, Ang Li, Zejian Yuan +2
We address the problem of decomposing a single image into reflectance and shading. The difficulty comes from the fact that the components of image---the surface albedo, the direct…