Papers with Code 아카이브

Autonomous Vehicles

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 15
평가표: 1
보존된 평가 기록: 2

Autonomous vehicles is the task of making a vehicle that can guide itself without human conduction.

Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.

<span style="color:grey; opacity: 0.6">( Image credit: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/qcraftai/simtrack

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Exploring Simple 3D Multi-Object Tracking for Autonomous Driving

https://github.com/qcraftai/tip

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Transcendental Idealism of Planner: Evaluating Perception from Planning Perspective for Autonomous Driving

https://github.com/qianhewu/point-cloud-smoothing

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TPC: Transformation-Specific Smoothing for Point Cloud Models

https://github.com/qiantianwen/nuscenes-qa

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NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

https://github.com/qimaqi/continuous-pose-in-nerf

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Continuous Pose for Monocular Cameras in Neural Implicit Representation

https://github.com/qingshufan/GeneA-SLAM2

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GeneA-SLAM2: Dynamic SLAM with AutoEncoder-Preprocessed Genetic Keypoints Resampling and Depth Variance-Guided Dynamic Region Removal

https://github.com/qinnzou/Robust-Lane-Detection

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Robust Lane Detection from Continuous Driving Scenes Using Deep Neural Networks

https://github.com/qiongwu86/joint-optimization-of-aoi-and-energy-consumption-in-nr-v2x-system-based-on-drl

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Joint Optimization of Age of Information and Energy Consumption in NR-V2X System based on Deep Reinforcement Learning

https://github.com/qiongwu86/ppo-based-vehicle-control-for-ramp-merging-scheme-assisted-by-enhanced-c-v2x

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PPO-Based Vehicle Control for Ramp Merging Scheme Assisted by Enhanced C-V2X

https://github.com/qiujumin/don-rl

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Decision-making and control with diffractive optical networks

https://github.com/qizs-bit/gspr

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GSPR: Multimodal Place Recognition Using 3D Gaussian Splatting for Autonomous Driving

https://github.com/qizs-bit/lrfusionpr

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LRFusionPR: A Polar BEV-Based LiDAR-Radar Fusion Network for Place Recognition

https://github.com/qualityminds/cistgcn

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Context-based Interpretable Spatio-Temporal Graph Convolutional Network for Human Motion Forecasting

https://github.com/quan-dao/apro3d-net

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Attention-based Proposals Refinement for 3D Object Detection

https://github.com/quangle2110/GAN_Mask-RCNN

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Instance Semantic Segmentation Benefits from Generative Adversarial Networks

https://github.com/queyrusi/pelta

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Mitigating Adversarial Attacks in Federated Learning with Trusted Execution Environments

https://github.com/qzhb/ubrv2a

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Uncertainty-boosted Robust Video Activity Anticipation

https://github.com/radar-lab/Lidar_Camera_Automatic_Calibration

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CalibRefine: Deep Learning-Based Online Automatic Targetless LiDAR-Camera Calibration with Iterative and Attention-Driven Post-Refinement

https://github.com/radar-lab/transrad

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TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection

https://github.com/radetzkyli/multi-v2x

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Multi-V2X: A Large Scale Multi-modal Multi-penetration-rate Dataset for Cooperative Perception

https://github.com/raffaelegalliera/melissa

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Collaborative Information Dissemination with Graph-based Multi-Agent Reinforcement Learning

https://github.com/raghavendersahdev/Free-Space

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Free Space Estimation using Occupancy Grids and Dynamic Object Detection

https://github.com/raileye3d/raileye3d_dataset

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RGB-D Railway Platform Monitoring and Scene Understanding for Enhanced Passenger Safety

https://github.com/rainmaker22/SMART

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SMART: Scalable Multi-agent Real-time Motion Generation via Next-token Prediction

https://github.com/ram95d/ovose

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OVOSE: Open-Vocabulary Semantic Segmentation in Event-Based Cameras

https://github.com/ramdrop/stun

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STUN: Self-Teaching Uncertainty Estimation for Place Recognition

https://github.com/rana2149/actnetformer

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ActNetFormer: Transformer-ResNet Hybrid Method for Semi-Supervised Action Recognition in Videos

https://github.com/raptor-msstate/xdecode

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X-DECODE: EXtreme Deblurring with Curriculum Optimization and Domain Equalization

https://github.com/rasd3/toda

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Semi-Supervised Domain Adaptation Using Target-Oriented Domain Augmentation for 3D Object Detection

https://github.com/raulsenaferreira/prdc_2021_sut_module

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Benchmarking Safety Monitors for Image Classifiers with Machine Learning

https://github.com/ravikt/gril

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Imitation Learning with Human Eye Gaze via Multi-Objective Prediction

https://github.com/raynbowy23/RNTransformer

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Enhancing Pedestrian Trajectory Prediction with Crowd Trip Information

https://github.com/raynbowy23/fedmeta-geolane

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Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection

https://github.com/rbgirshick/voc-dpm

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Scene-Specific Pedestrian Detection Based on Parallel Vision

https://github.com/rbokade/pytsc

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PyTSC: A Unified Platform for Multi-Agent Reinforcement Learning in Traffic Signal Control

https://github.com/rdeiaco/learning_lattice_planner

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Learning a Lattice Planner Control Set for Autonomous Vehicles

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.