84 citations · 235 across the 22 of their papers we have counts for
22 papers
SocialCircle: Learning the Angle-based Social Interaction Representation for Pedestrian Trajectory Prediction
Conghao Wong, Beihao Xia, Ziqian Zou +2
Analyzing and forecasting trajectories of agents like pedestrians and cars in complex scenes has become more and more significant in many intelligent systems and applications. The…
CSCNet: Contextual Semantic Consistency Network for Trajectory Prediction in Crowded Spaces
Beihao Xia, Conghao Wong, Qinmu Peng +2
Trajectory prediction aims to predict the movement trend of the agents like pedestrians, bikers, vehicles. It is helpful to analyze and understand human activities in crowded space…
TransZero: Attribute-guided Transformer for Zero-Shot Learning
Shiming Chen, Ziming Hong, Yang Liu +6
Zero-shot learning (ZSL) aims to recognize novel classes by transferring semantic knowledge from seen classes to unseen ones. Semantic knowledge is learned from attribute descripti…
HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning
Shiming Chen, Guo-Sen Xie, Yang Liu +5
Zero-shot learning (ZSL) tackles the unseen class recognition problem, transferring semantic knowledge from seen classes to unseen ones. Typically, to guarantee desirable knowledge…
View Vertically: A Hierarchical Network for Trajectory Prediction via Fourier Spectrums
Conghao Wong, Beihao Xia, Ziming Hong +5
Understanding and forecasting future trajectories of agents are critical for behavior analysis, robot navigation, autonomous cars, and other related applications. Previous methods…
FREE: Feature Refinement for Generalized Zero-Shot Learning
Shiming Chen, Wenjie Wang, Beihao Xia +4
Generalized zero-shot learning (GZSL) has achieved significant progress, with many efforts dedicated to overcoming the problems of visual-semantic domain gap and seen-unseen bias.…
MSN: Multi-Style Network for Trajectory Prediction
Conghao Wong, Beihao Xia, Qinmu Peng +2
Trajectory prediction aims to forecast agents' possible future locations considering their observations along with the video context. It is strongly needed by many autonomous platf…
Adaptive Matching of Kernel Means
Miao Cheng, Xinge You
As a promising step, the performance of data analysis and feature learning are able to be improved if certain pattern matching mechanism is available. One of the feasible solutions…
BGM: Building a Dynamic Guidance Map without Visual Images for Trajectory Prediction
Beihao Xia, Conghao Wong, Heng Li +3
Visual images usually contain the informative context of the environment, thereby helping to predict agents' behaviors. However, they hardly impose the dynamic effects on agents' a…
CDE-GAN: Cooperative Dual Evolution Based Generative Adversarial Network
Shiming Chen, Wenjie Wang, Beihao Xia +3
Generative adversarial networks (GANs) have been a popular deep generative model for real-world applications. Despite many recent efforts on GANs that have been contributed, mode c…
Modal Regression based Structured Low-rank Matrix Recovery for Multi-view Learning
Jiamiao Xu, Fangzhao Wang, Qinmu Peng +4
Low-rank Multi-view Subspace Learning (LMvSL) has shown great potential in cross-view classification in recent years. Despite their empirical success, existing LMvSL based methods…
A Spatial-Temporal Attentive Network with Spatial Continuity for Trajectory Prediction
Beihao Xia, Conghao Wang, Qinmu Peng +2
It remains challenging to automatically predict the multi-agent trajectory due to multiple interactions including agent to agent interaction and scene to agent interaction. Althoug…
Kernelized Similarity Learning and Embedding for Dynamic Texture Synthesis
Shiming Chen, Peng Zhang, Guo-Sen Xie +4
Dynamic texture (DT) exhibits statistical stationarity in the spatial domain and stochastic repetitiveness in the temporal dimension, indicating that different frames of DT possess…
Closed-Loop Adaptation for Weakly-Supervised Semantic Segmentation
Zhengqiang Zhang, Shujian Yu, Shi Yin +2
Weakly-supervised semantic segmentation aims to assign each pixel a semantic category under weak supervisions, such as image-level tags. Most of existing weakly-supervised semantic…
Fast and accurate reconstruction of HARDI using a 1D encoder-decoder convolutional network
Shi Yin, Zhengqiang Zhang, Qinmu Peng +1
High angular resolution diffusion imaging (HARDI) demands a lager amount of data measurements compared to diffusion tensor imaging, restricting its use in practice. In this work, w…
Fully-automatic segmentation of kidneys in clinical ultrasound images using a boundary distance regression network
Shi Yin, Zhengqiang Zhang, Hongming Li +5
It remains challenging to automatically segment kidneys in clinical ultrasound images due to the kidneys' varied shapes and image intensity distributions, although semi-automatic m…
Robust Visual Tracking using Multi-Frame Multi-Feature Joint Modeling
Peng Zhang, Shujian Yu, Jiamiao Xu +4
It remains a huge challenge to design effective and efficient trackers under complex scenarios, including occlusions, illumination changes and pose variations. To cope with this pr…
Automatic kidney segmentation in ultrasound images using subsequent boundary distance regression and pixelwise classification networks
Shi Yin, Qinmu Peng, Hongming Li +5
It remains challenging to automatically segment kidneys in clinical ultrasound (US) images due to the kidneys' varied shapes and image intensity distributions, although semi-automa…
Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition
Chaojian Yu, Xinyi Zhao, Qi Zheng +2
Fine-grained visual recognition is challenging because it highly relies on the modeling of various semantic parts and fine-grained feature learning. Bilinear pooling based models h…
Multi-view Common Component Discriminant Analysis for Cross-view Classification
Xinge You, Jiamiao Xu, Wei Yuan +3
Cross-view classification that means to classify samples from heterogeneous views is a significant yet challenging problem in computer vision. A promising approach to handle this p…
Coarse-to-Fine Salient Object Detection with Low-Rank Matrix Recovery
Qi Zheng, Shujian Yu, Xinge You +1
Low-Rank Matrix Recovery (LRMR) has recently been applied to saliency detection by decomposing image features into a low-rank component associated with background and a sparse comp…
Multi-view Hybrid Embedding: A Divide-and-Conquer Approach
Jiamiao Xu, Shujian Yu, Xinge You +3
We present a novel cross-view classification algorithm where the gallery and probe data come from different views. A popular approach to tackle this problem is the multi-view subsp…