Search Results for author: Xu Liu

Found 83 papers, 25 papers with code

Gait Lateral Network: Learning Discriminative and Compact Representations for Gait Recognition

1 code implementation ECCV 2020 Saihui Hou, Chunshui Cao, Xu Liu, Yongzhen Huang

Gait recognition aims at identifying different people by the walking patterns, which can be conducted at a long distance without the cooperation of subjects.

Gait Recognition

Low-rank Adaptation for Spatio-Temporal Forecasting

no code implementations11 Apr 2024 Weilin Ruan, Wei Chen, Xilin Dang, Jianxiang Zhou, Weichuang Li, Xu Liu, Yuxuan Liang

Spatio-temporal forecasting is crucial in real-world dynamic systems, predicting future changes using historical data from diverse locations.

Spatio-Temporal Forecasting

Hallucination Diversity-Aware Active Learning for Text Summarization

no code implementations2 Apr 2024 Yu Xia, Xu Liu, Tong Yu, Sungchul Kim, Ryan A. Rossi, Anup Rao, Tung Mai, Shuai Li

Large Language Models (LLMs) have shown propensity to generate hallucinated outputs, i. e., texts that are factually incorrect or unsupported.

Active Learning Hallucination +1

CACA Agent: Capability Collaboration based AI Agent

no code implementations22 Mar 2024 Peng Xu, Haoran Wang, Chuang Wang, Xu Liu

As AI Agents based on Large Language Models (LLMs) have shown potential in practical applications across various fields, how to quickly deploy an AI agent and how to conveniently expand the application scenario of AI agents has become a challenge.

Diffeomorphism Neural Operator for various domains and parameters of partial differential equations

no code implementations19 Feb 2024 Zhiwei Zhao, Changqing Liu, Yingguang Li, Zhibin Chen, Xu Liu

Neural operator models provide an efficient alternative by learning the governing physical laws directly from data in a class of PDEs with different parameters, but constrained in a fixed boundary (domain).

Operator learning

QAGait: Revisit Gait Recognition from a Quality Perspective

1 code implementation24 Jan 2024 Zengbin Wang, Saihui Hou, Man Zhang, Xu Liu, Chunshui Cao, Yongzhen Huang, Peipei Li, Shibiao Xu

Gait recognition is a promising biometric method that aims to identify pedestrians from their unique walking patterns.

Gait Recognition

TNANet: A Temporal-Noise-Aware Neural Network for Suicidal Ideation Prediction with Noisy Physiological Data

no code implementations23 Jan 2024 Niqi Liu, Fang Liu, Wenqi Ji, Xinxin Du, Xu Liu, Guozhen Zhao, Wenting Mu, Yong-Jin Liu

Current methods predominantly focus on image and text data or address artificially introduced noise, neglecting the complexities of natural noise in time-series analysis.

Binary Classification Photoplethysmography (PPG) +2

Geometric Prior Guided Feature Representation Learning for Long-Tailed Classification

no code implementations21 Jan 2024 Yanbiao Ma, Licheng Jiao, Fang Liu, Shuyuan Yang, Xu Liu, Puhua Chen

In this work, we propose to leverage the geometric information of the feature distribution of the well-represented head class to guide the model to learn the underlying distribution of the tail class.

Representation Learning

LLMs for Relational Reasoning: How Far are We?

no code implementations17 Jan 2024 Zhiming Li, Yushi Cao, Xiufeng Xu, Junzhe Jiang, Xu Liu, Yon Shin Teo, Shang-Wei Lin, Yang Liu

Large language models (LLMs) have revolutionized many areas (e. g. natural language processing, software engineering, etc.)

Common Sense Reasoning Decision Making +3

Towards the Unification of Generative and Discriminative Visual Foundation Model: A Survey

no code implementations15 Dec 2023 Xu Liu, Tong Zhou, Yuanxin Wang, Yuping Wang, Qinjingwen Cao, Weizhi Du, Yonghuan Yang, Junjun He, Yu Qiao, Yiqing Shen

The advent of foundation models, which are pre-trained on vast datasets, has ushered in a new era of computer vision, characterized by their robustness and remarkable zero-shot generalization capabilities.

Image Generation Image Segmentation +2

CLIPC8: Face liveness detection algorithm based on image-text pairs and contrastive learning

2 code implementations29 Nov 2023 Xu Liu, Shu Zhou, Yurong Song, Wenzhe Luo, Xin Zhang

To tackle this issue, we propose a face liveness detection method based on image-text pairs and contrastive learning, dividing liveness attack problems in the financial field into eight categories and using text information to describe the images of these eight types of attacks.

Contrastive Learning Face Recognition

Data-Centric Long-Tailed Image Recognition

no code implementations3 Nov 2023 Yanbiao Ma, Licheng Jiao, Fang Liu, Shuyuan Yang, Xu Liu, Puhua Chen

In the context of the long-tail scenario, models exhibit a strong demand for high-quality data.

Long-tail Learning

Towards Unifying Diffusion Models for Probabilistic Spatio-Temporal Graph Learning

no code implementations26 Oct 2023 Junfeng Hu, Xu Liu, Zhencheng Fan, Yuxuan Liang, Roger Zimmermann

Based on this proposal, we introduce Unified Spatio-Temporal Diffusion Models (USTD) to address the tasks uniformly within the uncertainty-aware diffusion framework.

Denoising Graph Learning

Orthogonal Uncertainty Representation of Data Manifold for Robust Long-Tailed Learning

no code implementations16 Oct 2023 Yanbiao Ma, Licheng Jiao, Fang Liu, Shuyuan Yang, Xu Liu, Lingling Li

The disadvantage is that these methods generally pursue models with balanced class accuracy on the data manifold, while ignoring the ability of the model to resist interference.

FastPoseGait: A Toolbox and Benchmark for Efficient Pose-based Gait Recognition

1 code implementation2 Sep 2023 Shibei Meng, Yang Fu, Saihui Hou, Chunshui Cao, Xu Liu, Yongzhen Huang

Our toolbox supports a set of cutting-edge pose-based gait recognition algorithms and a variety of related benchmarks.

Gait Recognition

AutoST: Training-free Neural Architecture Search for Spiking Transformers

no code implementations1 Jul 2023 Ziqing Wang, Qidong Zhao, Jinku Cui, Xu Liu, Dongkuan Xu

To address these limitations, we introduce AutoST, a training-free NAS method for Spiking Transformers, to rapidly identify high-performance Spiking Transformer architectures.

Neural Architecture Search

TorchBench: Benchmarking PyTorch with High API Surface Coverage

1 code implementation27 Apr 2023 Yueming Hao, Xu Zhao, Bin Bao, David Berard, Will Constable, Adnan Aziz, Xu Liu

TorchBench is able to comprehensively characterize the performance of the PyTorch software stack, guiding the performance optimization across models, PyTorch framework, and GPU libraries.

Benchmarking Vocal Bursts Intensity Prediction

Coupling Artificial Neurons in BERT and Biological Neurons in the Human Brain

no code implementations27 Mar 2023 Xu Liu, Mengyue Zhou, Gaosheng Shi, Yu Du, Lin Zhao, Zihao Wu, David Liu, Tianming Liu, Xintao Hu

Linking computational natural language processing (NLP) models and neural responses to language in the human brain on the one hand facilitates the effort towards disentangling the neural representations underpinning language perception, on the other hand provides neurolinguistics evidence to evaluate and improve NLP models.

Curvature-Balanced Feature Manifold Learning for Long-Tailed Classification

1 code implementation CVPR 2023 Yanbiao Ma, Licheng Jiao, Fang Liu, Shuyuan Yang, Xu Liu, Lingling Li

In this work, we systematically propose a series of geometric measurements for perceptual manifolds in deep neural networks, and then explore the effect of the geometric characteristics of perceptual manifolds on classification difficulty and how learning shapes the geometric characteristics of perceptual manifolds.

Classification Long-tail Learning

Unsupervised Gait Recognition with Selective Fusion

no code implementations19 Mar 2023 Xuqian Ren, Saihui Hou, Chunshui Cao, Xu Liu, Yongzhen Huang

So to make the pre-trained gait recognition model able to be fine-tuned on unlabeled datasets, we propose a new task: Unsupervised Gait Recognition (UGR).

Contrastive Learning Gait Recognition

Bi-level Multi-objective Evolutionary Learning: A Case Study on Multi-task Graph Neural Topology Search

no code implementations6 Feb 2023 Chao Wang, Licheng Jiao, Jiaxuan Zhao, Lingling Li, Xu Liu, Fang Liu, Shuyuan Yang

It is computationally expensive to determine which LL Pareto weight in the LL Pareto weight set is the most appropriate for each UL solution.

Decision Making Graph Classification +2

Do We Really Need Graph Neural Networks for Traffic Forecasting?

no code implementations30 Jan 2023 Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann

Spatio-temporal graph neural networks (STGNN) have become the most popular solution to traffic forecasting.

An In-Depth Exploration of Person Re-Identification and Gait Recognition in Cloth-Changing Conditions

2 code implementations CVPR 2023 Weijia Li, Saihui Hou, Chunjie Zhang, Chunshui Cao, Xu Liu, Yongzhen Huang, Yao Zhao

For the cloth-changing problem, video-based ReID is rarely studied due to the lack of a suitable cloth-changing benchmark, and gait recognition is often researched under controlled conditions.

16k Gait Recognition +1

Delving into Semantic Scale Imbalance

no code implementations30 Dec 2022 Yanbiao Ma, Licheng Jiao, Fang Liu, Yuxin Li, Shuyuan Yang, Xu Liu

Due to the prevalence of semantic scale imbalance, we propose semantic-scale-balanced learning, including a general loss improvement scheme and a dynamic re-weighting training framework that overcomes the challenge of calculating semantic scales in real-time during iterations.

Event-based Monocular Dense Depth Estimation with Recurrent Transformers

no code implementations6 Dec 2022 Xu Liu, Jianing Li, Xiaopeng Fan, Yonghong Tian

Event cameras, offering high temporal resolutions and high dynamic ranges, have brought a new perspective to address common challenges (e. g., motion blur and low light) in monocular depth estimation.

Event-based vision Monocular Depth Estimation

DWRSeg: Rethinking Efficient Acquisition of Multi-scale Contextual Information for Real-time Semantic Segmentation

no code implementations2 Dec 2022 Haoran Wei, Xu Liu, Shouchun Xu, Zhongjian Dai, Yaping Dai, Xiangyang Xu

In this method, the multi-rate depth-wise dilated convolutions take a simpler role in feature extraction: performing simple semantic-based morphological filtering with one desired receptive field in the second step based on each concise feature map of region form provided by the first step, to improve their efficiency.

Real-Time Semantic Segmentation

Deep Active Learning for Computer Vision: Past and Future

no code implementations27 Nov 2022 Rinyoichi Takezoe, Xu Liu, Shunan Mao, Marco Tianyu Chen, Zhanpeng Feng, Shiliang Zhang, Xiaoyu Wang

As an important data selection schema, active learning emerges as the essential component when iterating an Artificial Intelligence (AI) model.

Active Learning

Task-Agnostic Learning to Accomplish New Tasks

1 code implementation9 Sep 2022 Xianqi Zhang, Xingtao Wang, Xu Liu, Wenrui Wang, Xiaopeng Fan, Debin Zhao

Inspired by this observation, this paper proposes a task-agnostic learning method (TAL for short) that can learn fragmented knowledge from task-agnostic data to accomplish new tasks.

Imitation Learning Offline RL +1

Deep Learning-based Occluded Person Re-identification: A Survey

no code implementations29 Jul 2022 Yunjie Peng, Saihui Hou, Chunshui Cao, Xu Liu, Yongzhen Huang, Zhiqiang He

After that, we summarize and compare the performance of recent occluded person Re-ID methods on four popular datasets: Partial-ReID, Partial-iLIDS, Occluded-ReID, and Occluded-DukeMTMC.

Person Re-Identification

Progressive Feature Learning for Realistic Cloth-Changing Gait Recognition

no code implementations24 Jul 2022 Xuqian Ren, Saihui Hou, Chunshui Cao, Xu Liu, Yongzhen Huang

Furthermore, we propose a new framework that can be applied with off-the-shelf backbones to improve its performance in the Realistic Cloth-Changing problem with Progressive Feature Learning.

Gait Recognition

Reliability Analysis of Complex Multi-State System Based on Universal Generating Function and Bayesian Network

no code implementations15 Jun 2022 Xu Liu, Wen Yao, Xiaohu Zheng, Yingchun Xu

To overcome the respective defects of UGF and BN, a novel reliability analysis method called UGF-BN is proposed for the complex MSS.

Computational Efficiency

Bayesian Physics-Informed Extreme Learning Machine for Forward and Inverse PDE Problems with Noisy Data

no code implementations14 May 2022 Xu Liu, Wen Yao, Wei Peng, Weien Zhou

Besides, for inverse PDE problems, problem parameters considered as new output layer weights are unified in a framework with forward PDE problems.

Uncertainty Quantification

Mars Entry Trajectory Planning with Range Discretization and Successive Convexification

no code implementations24 Jan 2022 Xu Liu, Shuang Li, Ming Xin

The virtual control and adaptive trust-region techniques are employed to improve the accuracy, robustness, and computation efficiency of the algorithm.

Numerical Integration Trajectory Planning

Temperature Field Inversion of Heat-Source Systems via Physics-Informed Neural Networks

1 code implementation18 Jan 2022 Xu Liu, Wei Peng, Zhiqiang Gong, Weien Zhou, Wen Yao

In this work, we develop a physics-informed neural network-based temperature field inversion (PINN-TFI) method to solve the TFI-HSS task and a coefficient matrix condition number based position selection of observations (CMCN-PSO) method to select optima positions of noise observations.

Data Augmentation For Medical MR Image Using Generative Adversarial Networks

no code implementations29 Nov 2021 Panjian Huang, Xu Liu, Yongzhen Huang

Our results show that PGGAN-SSIM successfully generates 256x256 realistic brain tumor MR images which fill the real image distribution uncovered by the original dataset.

Data Augmentation MS-SSIM +1

Residual fourier neural operator for thermochemical curing of composites

no code implementations15 Nov 2021 Gengxiang Chen, Yingguang Li, Xu Liu, Qinglu Meng, Jing Zhou, Xiaozhong Hao

During the curing process of composites, the temperature history heavily determines the evolutions of the field of degree of cure as well as the residual stress, which will further influence the mechanical properties of composite, thus it is important to simulate the real temperature history to optimize the curing process of composites.

Relative Entropy Gradient Sampler for Unnormalized Distributions

no code implementations6 Oct 2021 Xingdong Feng, Yuan Gao, Jian Huang, Yuling Jiao, Xu Liu

We propose a relative entropy gradient sampler (REGS) for sampling from unnormalized distributions.

When Do Contrastive Learning Signals Help Spatio-Temporal Graph Forecasting?

1 code implementation26 Aug 2021 Xu Liu, Yuxuan Liang, Chao Huang, Yu Zheng, Bryan Hooi, Roger Zimmermann

In view of this, one may ask: can we leverage the additional signals from contrastive learning to alleviate data scarcity, so as to benefit STG forecasting?

Contrastive Learning Data Augmentation +2

A novel meta-learning initialization method for physics-informed neural networks

no code implementations23 Jul 2021 Xu Liu, Xiaoya Zhang, Wei Peng, Weien Zhou, Wen Yao

Inspired by this idea, we propose the new Reptile initialization to sample more tasks from the parameterized PDEs and adapt the penalty term of the loss.

Meta-Learning

Deployment Optimization for Meta-material Based Internet of Things

no code implementations3 Jul 2021 Xu Liu, Jingzhi Hu, Hongliang Zhang, Boya Di, Lingyang Song

It is a challenge to optimize the positions of the Meta-IoT devices to ensure sensing accuracy of 3D environmental conditions.

One Model for All Quantization: A Quantized Network Supporting Hot-Swap Bit-Width Adjustment

no code implementations4 May 2021 Qigong Sun, Xiufang Li, Yan Ren, Zhongjian Huang, Xu Liu, Licheng Jiao, Fang Liu

When the precision of quantization is adjusted, it is necessary to fine-tune the quantized model or minimize the quantization noise, which brings inconvenience in practical applications.

Quantization

Exploring Imitation Learning for Autonomous Driving with Feedback Synthesizer and Differentiable Rasterization

no code implementations2 Mar 2021 Jinyun Zhou, Rui Wang, Xu Liu, Yifei Jiang, Shu Jiang, Jiaming Tao, Jinghao Miao, Shiyu Song

Detailed ablation and visualization analysis are included to further demonstrate each of our proposed modules' effectiveness in our method.

Autonomous Driving Data Augmentation +1 Robotics

Turbulence suppression by streamwise-varying wall rotation in pipe flow

no code implementations6 Jan 2021 Xu Liu, Hongbo Zhu, Rui Wang, Yan Bao, Dai Zhou, Zhaolong Han, Chuanqing Zhou, Yegao Qu, Hui Xu

Two control parameters, which are velocity amplitude and wavelength, are considered.

Fluid Dynamics

Deep-Learned Broadband Encoding Stochastic Filters for Computational Spectroscopic Instruments

no code implementations17 Dec 2020 Hongya Song, Yaoguang Ma, Yubing Han, Weidong Shen, Wenyi Zhang, Yanghui Li, Xu Liu, Yifan Peng, Xiang Hao

Computational spectroscopic instruments with Broadband Encoding Stochastic (BEST) filters allow the reconstruction of the spectrum at high precision with only a few filters.

Instrumentation and Detectors

Group Contextual Encoding for 3D Point Clouds

1 code implementation NeurIPS 2020 Xu Liu, Chengtao Li, Jian Wang, Jingbo Wang, Boxin Shi, Xiaodong He

In this work, we extended the contextual encoding layer that was originally designed for 2D tasks to 3D Point Cloud scenarios.

Scene Understanding

Place Recognition in Forests with Urquhart Tessellations

1 code implementation23 Sep 2020 Guilherme V. Nardari, Avraham Cohen, Steven W. Chen, Xu Liu, Vaibhav Arcot, Roseli A. F. Romero, Vijay Kumar

In this letter, we present a novel descriptor based on Urquhart tessellations derived from the position of trees in a forest.

Loop Closure Detection Position

Variational Inference-Based Dropout in Recurrent Neural Networks for Slot Filling in Spoken Language Understanding

no code implementations23 Aug 2020 Jun Qi, Xu Liu, Javier Tejedor

This paper proposes to generalize the variational recurrent neural network (RNN) with variational inference (VI)-based dropout regularization employed for the long short-term memory (LSTM) cells to more advanced RNN architectures like gated recurrent unit (GRU) and bi-directional LSTM/GRU.

slot-filling Slot Filling +2

The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems

1 code implementation14 Jun 2020 Sixu Hu, Yuan Li, Xu Liu, Qinbin Li, Zhaomin Wu, Bingsheng He

This paper presents and characterizes an Open Application Repository for Federated Learning (OARF), a benchmark suite for federated machine learning systems.

Federated Learning

SLOAM: Semantic Lidar Odometry and Mapping for Forest Inventory

no code implementations29 Dec 2019 Steven W. Chen, Guilherme V. Nardari, Elijah S. Lee, Chao Qu, Xu Liu, Roseli A. F. Romero, Vijay Kumar

This paper describes an end-to-end pipeline for tree diameter estimation based on semantic segmentation and lidar odometry and mapping.

Segmentation Semantic Segmentation

PolSF: PolSAR image dataset on San Francisco

2 code implementations16 Dec 2019 Xu Liu, Licheng Jiao, Fang Liu

In this paper, we have collected five open polarimetric SAR images, which are images of the San Francisco area.

Image Classification

Directed-Weighting Group Lasso for Eltwise Blocked CNN Pruning

no code implementations21 Oct 2019 Ke Zhan, Shimiao Jiang, Yu Bai, Yi Li, Xu Liu, Zhuoran Xu

Eltwise layer is a commonly used structure in the multi-branch deep learning network.

A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection

1 code implementation23 Jul 2019 Qinbin Li, Zeyi Wen, Zhaomin Wu, Sixu Hu, Naibo Wang, Yuan Li, Xu Liu, Bingsheng He

By systematically summarizing the existing federated learning systems, we present the design factors, case studies, and future research opportunities.

BIG-bench Machine Learning Federated Learning +1

PolSAR Image Classification based on Polarimetric Scattering Coding and Sparse Support Matrix Machine

no code implementations17 Jun 2019 Xu Liu, Licheng Jiao, Dan Zhang, Fang Liu

In this paper, a novel POLSAR image classification method is proposed based on polarimetric scattering coding and sparse support matrix machine.

Classification General Classification +1

Semi-supervised Complex-valued GAN for Polarimetric SAR Image Classification

no code implementations9 Jun 2019 Qigong Sun, Xiufang Li, Lingling Li, Xu Liu, Fang Liu, Licheng Jiao

However, their interpretation faces some challenges, e. g., deficiency of labeled data, inadequate utilization of data information and so on.

Classification General Classification +2

An End-to-End Network for Panoptic Segmentation

no code implementations CVPR 2019 Huanyu Liu, Chao Peng, Changqian Yu, Jingbo Wang, Xu Liu, Gang Yu, Wei Jiang

Panoptic segmentation, which needs to assign a category label to each pixel and segment each object instance simultaneously, is a challenging topic.

Panoptic Segmentation Segmentation

Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect

1 code implementation11 Mar 2019 Ang Li, Shuaiwen Leon Song, Jieyang Chen, Jiajia Li, Xu Liu, Nathan Tallent, Kevin Barker

High performance multi-GPU computing becomes an inevitable trend due to the ever-increasing demand on computation capability in emerging domains such as deep learning, big data and planet-scale simulations.

Hardware Architecture Distributed, Parallel, and Cluster Computing Networking and Internet Architecture Performance

Deep Adaptive Proposal Network for Object Detection in Optical Remote Sensing Images

no code implementations19 Jul 2018 Lin Cheng, Xu Liu, Lingling Li, Licheng Jiao, Xu Tang

More recently, a two-stage detector Faster R-CNN is proposed and demonstrated to be a promising tool for object detection in optical remote sensing images, while the sparse and dense characteristic of objects in remote sensing images is complexity.

Object object-detection +2

Polarimetric Convolutional Network for PolSAR Image Classification

1 code implementation9 Jul 2018 Xu Liu, Licheng Jiao, Xu Tang, Qigong Sun, Dan Zhang

Based on sparse scattering coding and convolution neural network, the polarimetric convolutional network is proposed to classify PolSAR images by making full use of polarimetric information.

Classification General Classification +1

Robust Fruit Counting: Combining Deep Learning, Tracking, and Structure from Motion

no code implementations1 Apr 2018 Xu Liu, Steven W. Chen, Shreyas Aditya, Nivedha Sivakumar, Sandeep Dcunha, Chao Qu, Camillo J. Taylor, Jnaneshwar Das, Vijay Kumar

We present a novel fruit counting pipeline that combines deep segmentation, frame to frame tracking, and 3D localization to accurately count visible fruits across a sequence of images.

Deep Hashing with Category Mask for Fast Video Retrieval

1 code implementation22 Dec 2017 Xu Liu, Lili Zhao, Dajun Ding, Yajiao Dong

This paper proposes an end-to-end deep hashing framework with category mask for fast video retrieval.

Code Generation Deep Hashing +2

DualNet: Learn Complementary Features for Image Recognition

1 code implementation ICCV 2017 Saihui Hou, Xu Liu, Zilei Wang

Here two parallel neural networks are coordinated to learn complementary features and thus a wider network is constructed.

Multiple-Kernel Based Vehicle Tracking Using 3D Deformable Model and Camera Self-Calibration

no code implementations22 Aug 2017 Zheng Tang, Gaoang Wang, Tao Liu, Young-Gun Lee, Adwin Jahn, Xu Liu, Xiaodong He, Jenq-Neng Hwang

In this challenge, we propose a model-based vehicle localization method, which builds a kernel at each patch of the 3D deformable vehicle model and associates them with constraints in 3D space.

Ensemble Learning object-detection +1

Unsupervised Submodular Rank Aggregation on Score-based Permutations

1 code implementation4 Jul 2017 Jun Qi, Xu Liu, Javier Tejedor, Shunsuke Kamijo

Unsupervised rank aggregation on score-based permutations, which is widely used in many applications, has not been deeply explored yet.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

Highway Vehicle Counting in Compressed Domain

no code implementations CVPR 2016 Xu Liu, Zilei Wang, Jiashi Feng, Hongsheng Xi

HCR hierarchically divides the traffic scenes into different cases according to vehicle density, such that the broad-variation characteristics of traffic scenes can be better approximated.

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