780 citations · 1.8k across the 45 of their papers we have counts for
18 papers · 1 filter
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-…
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…
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…
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…
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…
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…
Adding Attentiveness to the Neurons in Recurrent Neural Networks
Pengfei Zhang, Jianru Xue, Cuiling Lan +3
Recurrent neural networks (RNNs) are capable of modeling the temporal dynamics of complex sequential information. However, the structures of existing RNN neurons mainly focus on co…
View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition
Pengfei Zhang, Cuiling Lan, Junliang Xing +3
Skeleton-based human action recognition has recently attracted increasing attention thanks to the accessibility and the popularity of 3D skeleton data. One of the key challenges in…
A Novel Brain Decoding Method: a Correlation Network Framework for Revealing Brain Connections
Siyu Yu, Nanning Zheng, Yongqiang Ma +2
Brain decoding is a hot spot in cognitive science, which focuses on reconstructing perceptual images from brain activities. Analyzing the correlations of collected data from human…
Associations among Image Assessments as Cost Functions in Linear Decomposition: MSE, SSIM, and Correlation Coefficient
Jianji Wang, Nanning Zheng, Badong Chen +1
The traditional methods of image assessment, such as mean squared error (MSE), signal-to-noise ratio (SNR), and Peak signal-to-noise ratio (PSNR), are all based on the absolute err…
View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data
Pengfei Zhang, Cuiling Lan, Junliang Xing +3
Skeleton-based human action recognition has recently attracted increasing attention due to the popularity of 3D skeleton data. One main challenge lies in the large view variations…
Salient Object Detection: A Discriminative Regional Feature Integration Approach
Huaizu Jiang, Zejian Yuan, Ming-Ming Cheng +3
Salient object detection has been attracting a lot of interest, and recently various heuristic computational models have been designed. In this paper, we formulate saliency map com…