62 citations · 250 across the 38 of their papers we have counts for
13 papers · 1 filter
RBFormer: Improve Adversarial Robustness of Transformer by Robust Bias
Hao Cheng, Jinhao Duan, Hui Li +6
Recently, there has been a surge of interest and attention in Transformer-based structures, such as Vision Transformer (ViT) and Vision Multilayer Perceptron (VMLP). Compared with…
Gaining the Sparse Rewards by Exploring Lottery Tickets in Spiking Neural Network
Hao Cheng, Jiahang Cao, Erjia Xiao +2
Deploying energy-efficient deep learning algorithms on computational-limited devices, such as robots, is still a pressing issue for real-world applications. Spiking Neural Networks…
Tracing the Influence of Predecessors on Trajectory Prediction
Mengmeng Liu, Hao Cheng, Michael Ying Yang
In real-world traffic scenarios, agents such as pedestrians and car drivers often observe neighboring agents who exhibit similar behavior as examples and then mimic their actions t…
An End-to-End Framework of Road User Detection, Tracking, and Prediction from Monocular Images
Hao Cheng, Mengmeng Liu, Lin Chen
Perception that involves multi-object detection and tracking, and trajectory prediction are two major tasks of autonomous driving. However, they are currently mostly studied separa…
LaplaceConfidence: a Graph-based Approach for Learning with Noisy Labels
Mingcai Chen, Yuntao Du, Wei Tang +4
In real-world applications, perfect labels are rarely available, making it challenging to develop robust machine learning algorithms that can handle noisy labels. Recent methods ha…
Lattice-Aided Extraction of Spread-Spectrum Hidden Data
Fan Yang, Shanxiang Lyu, Hao Cheng +2
This paper discusses the problem of extracting spread spectrum hidden data from the perspective of lattice decoding. Since the conventional blind extraction scheme multi-carrier it…
Evaluating the Efficacy of Length-Controllable Machine Translation
Hao Cheng, Meng Zhang, Weixuan Wang +3
Length-controllable machine translation is a type of constrained translation. It aims to contain the original meaning as much as possible while controlling the length of the transl…
End-to-end Training and Decoding for Pivot-based Cascaded Translation Model
Hao Cheng, Meng Zhang, Liangyou Li +2
Utilizing pivot language effectively can significantly improve low-resource machine translation. Usually, the two translation models, source-pivot and pivot-target, are trained ind…
Is Silent eHMI Enough? A Passenger-Centric Study on Effective eHMI for Autonomous Personal Mobility Vehicles in the Field
Hailong Liu, Yang Li, Zhe Zeng +3
Autonomous Personal Mobility Vehicle (APMV) is a miniaturized autonomous vehicle designed to provide short-distance mobility to everyone in pedestrian-rich environments. By the cha…
LAformer: Trajectory Prediction for Autonomous Driving with Lane-Aware Scene Constraints
Mengmeng Liu, Hao Cheng, Lin Chen +5
Trajectory prediction for autonomous driving must continuously reason the motion stochasticity of road agents and comply with scene constraints. Existing methods typically rely on…
ForceFormer: Exploring Social Force and Transformer for Pedestrian Trajectory Prediction
Weicheng Zhang, Hao Cheng, Fatema T. Johora +1
Predicting trajectories of pedestrians based on goal information in highly interactive scenes is a crucial step toward Intelligent Transportation Systems and Autonomous Driving. Th…
ShadowFormer: Global Context Helps Image Shadow Removal
Lanqing Guo, Siyu Huang, Ding Liu +2
Recent deep learning methods have achieved promising results in image shadow removal. However, most of the existing approaches focus on working locally within shadow and non-shadow…
Generating Evidential BEV Maps in Continuous Driving Space
Yunshuang Yuan, Hao Cheng, Michael Ying Yang +1
Safety is critical for autonomous driving, and one aspect of improving safety is to accurately capture the uncertainties of the perception system, especially knowing the unknown. D…