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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/valeoai/LearningByCheating

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End-to-End Model-Free Reinforcement Learning for Urban Driving using Implicit Affordances

https://github.com/valeoai/MFEval

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Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?

https://github.com/valeoai/MVRSS

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Multi-View Radar Semantic Segmentation

https://github.com/valeoai/VideoActionModel

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VaViM and VaVAM: Autonomous Driving through Video Generative Modeling

https://github.com/valeoai/WoodScape

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WoodScape: A multi-task, multi-camera fisheye dataset for autonomous driving

https://github.com/valeoai/WoodScape/tree/master/omnidet

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OmniDet: Surround View Cameras based Multi-task Visual Perception Network for Autonomous Driving

https://github.com/valeoai/also

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ALSO: Automotive Lidar Self-supervision by Occupancy estimation

https://github.com/valeoai/cab

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Raising context awareness in motion forecasting

https://github.com/valeoai/carrada_dataset

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CARRADA Dataset: Camera and Automotive Radar with Range-Angle-Doppler Annotations

https://github.com/valeoai/gaussrender

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GaussRender: Learning 3D Occupancy with Gaussian Rendering

https://github.com/valeoai/genval

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Reliability in Semantic Segmentation: Can We Use Synthetic Data?

https://github.com/valeoai/mf_awta

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Annealed Winner-Takes-All for Motion Forecasting

https://github.com/valeoai/octet

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OCTET: Object-aware Counterfactual Explanations

https://github.com/valeoai/rangevit

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RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving

https://github.com/valeoai/regents

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ReGentS: Real-World Safety-Critical Driving Scenario Generation Made Stable

https://github.com/valeoai/scalr

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Three Pillars improving Vision Foundation Model Distillation for Lidar

https://github.com/valeoai/slidr

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Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data

https://github.com/valeoai/v-max

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V-Max: A Reinforcement Learning Framework for Autonomous Driving

https://github.com/valeoai/valeo4cast

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Valeo4Cast: A Modular Approach to End-to-End Forecasting

https://github.com/valeoai/waffleiron

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Using a Waffle Iron for Automotive Point Cloud Semantic Segmentation

https://github.com/valeoai/xmuda

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xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation

https://github.com/valeoai/xmuda_journal

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Cross-modal Learning for Domain Adaptation in 3D Semantic Segmentation

https://github.com/vcl-iisc/data-free-defense-at-test-time

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DAD++: Improved Data-free Test Time Adversarial Defense

https://github.com/vcl-iisc/improved-data-free-test-time-adversarial-defense

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DAD++: Improved Data-free Test Time Adversarial Defense

https://github.com/vdblm/ExPerior

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Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity

https://github.com/vdigpku/bev-mae

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BEV-MAE: Bird's Eye View Masked Autoencoders for Point Cloud Pre-training in Autonomous Driving Scenarios

https://github.com/vdigpku/drivinggaussian

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DrivingGaussian: Composite Gaussian Splatting for Surrounding Dynamic Autonomous Driving Scenes

https://github.com/vdigpku/henet

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HENet: Hybrid Encoding for End-to-end Multi-task 3D Perception from Multi-view Cameras

https://github.com/vdigpku/rcbevdet

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RCBEVDet: Radar-camera Fusion in Bird's Eye View for 3D Object Detection

https://github.com/vdigpku/teocc

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TEOcc: Radar-camera Multi-modal Occupancy Prediction via Temporal Enhancement

https://github.com/velatkilic/LISA

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Lidar Light Scattering Augmentation (LISA): Physics-based Simulation of Adverse Weather Conditions for 3D Object Detection

https://github.com/velor2012/tdo-dif

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Unsupervised Foggy Scene Understanding via Self Spatial-Temporal Label Diffusion

https://github.com/victoryxl/replenishmentenv

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A Versatile Multi-Agent Reinforcement Learning Benchmark for Inventory Management

https://github.com/viktorkare/bevf

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Towards a Robust Sensor Fusion Step for 3D Object Detection on Corrupted Data

https://github.com/vincentqqb/priorlane

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PriorLane: A Prior Knowledge Enhanced Lane Detection Approach Based on Transformer

https://github.com/virtualnew/mid_dataset

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MID: A Comprehensive Shore-Based Dataset for Multi-Scale Dense Ship Occlusion and Interaction Scenarios

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