当前位置: 首页 > article >正文

CVPR 2024 自动驾驶方向总汇

1、Automated Driving(自动驾驶)      

  • Bezier Everywhere All at Once: Learning Drivable Lanes as Bezier Graphs
    ⭐code
  • SparseOcc: Rethinking Sparse Latent Representation for Vision-Based Semantic Occupancy Prediction
  • 自动驾驶
    • Accurate Training Data for Occupancy Map Prediction in Automated Driving Using Evidence Theory
    • VLP: Vision Language Planning for Autonomous Driving
    • Collaborative Semantic Occupancy Prediction with Hybrid Feature Fusion in Connected Automated Vehicles
    • DrivingGaussian: Composite Gaussian Splatting for Surrounding Dynamic Autonomous Driving Scenes
    • Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous and Instruction-guided Driving
    • DualAD: Disentangling the Dynamic and Static World for End-to-End Driving
      🏠project
    • UniPAD: A Universal Pre-training Paradigm for Autonomous Driving
      ⭐code
    • Generalized Predictive Model for Autonomous Driving
      ⭐code
    • Cam4DOcc: Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications
    • ChatScene: Knowledge-Enabled Safety-Critical Scenario Generation for Autonomous Vehicles
    • Holistic Autonomous Driving Understanding by Bird's-Eye-View Injected Multi-Modal Large Models
    • LMDrive: Closed-Loop End-to-End Driving with Large Language Models
      ⭐code
      🏠project
    • Feedback-Guided Autonomous Driving
    • PARA-Drive: Parallelized Architecture for Real-time Autonomous Driving
    • Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving
      ⭐code
    • On the Road to Portability: Compressing End-to-End Motion Planner for Autonomous Driving
    • Visual Point Cloud Forecasting enables Scalable Autonomous Driving
      ⭐code
    • Adaptive Fusion of Single-View and Multi-View Depth for Autonomous Driving
      ⭐code
    • CLIP-BEVFormer: Enhancing Multi-View Image-Based BEV Detector with Ground Truth Flow
    • Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous Driving
    • AIDE: An Automatic Data Engine for Object Detection in Autonomous Driving
    • NeuRAD: Neural Rendering for Autonomous Driving
      ⭐code
      🏠project
    • Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving
      ⭐code
      🏠project
    • Editable Scene Simulation for Autonomous Driving via Collaborative LLM-Agents
      ⭐code
      🏠project
    • 3D LiDAR Mapping in Dynamic Environments using a 4D Implicit Neural Representation
      ⭐code
    • PACER+: On-Demand Pedestrian Animation Controller in Driving Scenarios
      ⭐code
      📺video
    • Bootstrapping Autonomous Driving Radars with Self-Supervised Learning
      ⭐code
    • SynFog: A Photo-realistic Synthetic Fog Dataset based on End-to-end Imaging Simulation for Advancing Real-World Defogging in Autonomous Driving自动驾驶去雾
  • 轨迹预测
    • Pose-Transformed Equivariant Network for 3D Point Trajectory Prediction
    • Adversarial Backdoor Attack by Naturalistic Data Poisoning on Trajectory Prediction in Autonomous Driving
    • CaDeT: a Causal Disentanglement Approach for Robust Trajectory Prediction in Autonomous Driving
    • Higher-order Relational Reasoning for Pedestrian Trajectory Prediction
    • Density-Adaptive Model Based on Motif Matrix for Multi-Agent Trajectory Prediction
    • GigaTraj: Predicting Long-term Trajectories of Hundreds of Pedestrians in Gigapixel Complex Scenes
    • ERMVP: Communication-Efficient and Collaboration-Robust Multi-Vehicle Perception in Challenging Environments
    • HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attention
      ⭐code
      👍VILP
    • Adapting to Length Shift: FlexiLength Network for Trajectory Prediction
    • OOSTraj: Out-of-Sight Trajectory Prediction With Vision-Positioning Denoising
      ⭐code
    • SocialCircle: Learning the Angle-based Social Interaction Representation for Pedestrian Trajectory Prediction行人轨迹预测
    • T4P: Test-Time Training of Trajectory Prediction via Masked Autoencoder and Actor-specific Token Memory
      ⭐code
    • Self-Supervised Class-Agnostic Motion Prediction with Spatial and Temporal Consistency Regularizations
    • SmartRefine: An Scenario-Adaptive Refinement Framework for Efficient Motion Prediction
      ⭐code
    • Producing and Leveraging Online Map Uncertainty in Trajectory Prediction
    • SingularTrajectory: Universal Trajectory Predictor Using Diffusion Model
      ⭐code
    • Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Prediction
      ⭐code
    • Quantifying Uncertainty in Motion Prediction with Variational Bayesian Mixture
      ⭐code
  • 车道线检测
    • LaneCPP: Continuous 3D Lane Detection using Physical Priors
    • Lane2Seq: Towards Unified Lane Detection via Sequence Generation
      🏠project
  • 车载凝视估计
    • What Do You See in Vehicle? Comprehensive Vision Solution for In-Vehicle Gaze Estimation
      🏠project
  • 3D Occupancy Prediction
    • COTR: Compact Occupancy TRansformer for Vision-based 3D Occupancy Prediction
      ⭐code
    • SelfOcc: Self-Supervised Vision-Based 3D Occupancy Prediction
      ⭐code
    • StreamingFlow: Streaming Occupancy Forecasting with Asynchronous Multi-modal Data Streams via Neural Ordinary Differential Equation 车辆重识别
    • Day-Night Cross-domain Vehicle Re-identification

http://www.kler.cn/a/505003.html

相关文章:

  • 【Sql递归查询】Mysql、Oracle、SQL Server、PostgreSQL 实现递归查询的区别与案例(详解)
  • 【Rust自学】12.2. 读取文件
  • HTML实战课堂之启动动画弹窗
  • Redis复制(replica)
  • Sonatype Nexus OSS 构建私有docker 仓库
  • 【汇编】x86汇编编程寄存器资源心中有数
  • RHCE的基本学习路线
  • Leetcode 2140. 解决智力问题 动态规划
  • 图解Git——分支管理《Pro Git》
  • Transformer架构和Transformers 库和Hugging Face
  • 【Python】第一弹---解锁编程新世界:深入理解计算机基础与Python入门指南
  • MongoDB 学习指南与资料分享
  • 面向对象三大特征之一——多态【红色标记】
  • c语言-嵌入式专辑~
  • ASP.NET Core - 依赖注入(三)
  • CF 230A.Dragons(Java实现)
  • Golang——GPM调度器
  • uniapp实现“到这儿去”、拨打电话功能
  • 【鸿蒙Next】protobuf如何使用
  • [MySQL | 二、基本数据类型]
  • Scikit-Learn快速入门
  • nginx 配置ssl_dhparam好处及缺点
  • 怎样应对发现的小红书笔记详情API安全风险?
  • 心有花木,向阳而生:拥抱生活的无限可能
  • ADC(Analog-to-digital converter)模拟-数字转换器
  • c++领域展开第十二幕——类和对象(STL简介——简单了解STL)超详细!!!!