66 citations · 151 across the 18 of their papers we have counts for
19 papers
Reverberation: Learning the Latencies Before Forecasting Trajectories
Conghao Wong, Ziqian Zou, Beihao Xia +1
Bridging the past to the future, connecting agents both spatially and temporally, lies at the core of the trajectory prediction task. Despite great efforts, it remains challenging…
Pedestrian Trajectory Prediction Based on Social Interactions Learning With Random Weights
Jiajia Xie, Sheng Zhang, Beihao Xia +5
Pedestrian trajectory prediction is a critical technology in the evolution of self-driving cars toward complete artificial intelligence. Over recent years, focusing on the trajecto…
Who Walks With You Matters: Perceiving Social Interactions with Groups for Pedestrian Trajectory Prediction
Ziqian Zou, Conghao Wong, Beihao Xia +2
Understanding and anticipating human movement has become more critical and challenging in diverse applications such as autonomous driving and surveillance. The complex interactions…
Resonance: Learning to Predict Social-Aware Pedestrian Trajectories as Co-Vibrations
Conghao Wong, Ziqian Zou, Beihao Xia +1
Learning to forecast trajectories of intelligent agents has caught much more attention recently. However, it remains a challenge to accurately account for agents' intentions and so…
SocialCircle+: Learning the Angle-based Conditioned Interaction Representation for Pedestrian Trajectory Prediction
Conghao Wong, Beihao Xia, Ziqian Zou +1
Trajectory prediction is a crucial aspect of understanding human behaviors. Researchers have made efforts to represent socially interactive behaviors among pedestrians and utilize…
Ranking Distillation for Open-Ended Video Question Answering with Insufficient Labels
Tianming Liang, Chaolei Tan, Beihao Xia +2
This paper focuses on open-ended video question answering, which aims to find the correct answers from a large answer set in response to a video-related question. This is essential…
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…
Efficient Backdoor Attacks for Deep Neural Networks in Real-world Scenarios
Ziqiang Li, Hong Sun, Pengfei Xia +4
Recent deep neural networks (DNNs) have came to rely on vast amounts of training data, providing an opportunity for malicious attackers to exploit and contaminate the data to carry…
A Proxy Attack-Free Strategy for Practically Improving the Poisoning Efficiency in Backdoor Attacks
Ziqiang Li, Hong Sun, Pengfei Xia +6
Poisoning efficiency is crucial in poisoning-based backdoor attacks, as attackers aim to minimize the number of poisoning samples while maximizing attack efficacy. Recent studies h…
Another Vertical View: A Hierarchical Network for Heterogeneous Trajectory Prediction via Spectrums
Beihao Xia, Conghao Wong, Duanquan Xu +2
With the fast development of AI-related techniques, the applications of trajectory prediction are no longer limited to easier scenes and trajectories. More and more trajectories wi…
TODE-Trans: Transparent Object Depth Estimation with Transformer
Kang Chen, Shaochen Wang, Beihao Xia +3
Transparent objects are widely used in industrial automation and daily life. However, robust visual recognition and perception of transparent objects have always been a major chall…
A Comprehensive Survey on Data-Efficient GANs in Image Generation
Ziqiang Li, Beihao Xia, Jing Zhang +2
Generative Adversarial Networks (GANs) have achieved remarkable achievements in image synthesis. These successes of GANs rely on large scale datasets, requiring too much cost. With…
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…
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…
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…
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…