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/synsin0/srcn3d

공식 코드

SRCN3D: Sparse R-CNN 3D for Compact Convolutional Multi-View 3D Object Detection and Tracking

https://github.com/synsin0/streamingflow

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StreamingFlow: Streaming Occupancy Forecasting with Asynchronous Multi-modal Data Streams via Neural Ordinary Differential Equation

https://github.com/syqlyx/StructVPR

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StructVPR++: Distill Structural and Semantic Knowledge with Weighting Samples for Visual Place Recognition

https://github.com/syscv/lidar_snow_sim

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LiDAR Snowfall Simulation for Robust 3D Object Detection

https://github.com/syscv/trafficbots

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TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction

https://github.com/t3as/mad-arl

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Adversarial Deep Reinforcement Learning for Improving the Robustness of Multi-agent Autonomous Driving Policies

https://github.com/t3as/remav

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ReMAV: Reward Modeling of Autonomous Vehicles for Finding Likely Failure Events

https://github.com/tabguigui/fiptr

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FipTR: A Simple yet Effective Transformer Framework for Future Instance Prediction in Autonomous Driving

https://github.com/taco-group/LangCoop

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LangCoop: Collaborative Driving with Language

https://github.com/taco-group/autotrust

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AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving

https://github.com/taco-group/drama-x

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DRAMA-X: A Fine-grained Intent Prediction and Risk Reasoning Benchmark For Driving

https://github.com/taco-group/genai4ad

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Generative AI for Autonomous Driving: Frontiers and Opportunities

https://github.com/taco-group/openemma

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OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Driving

https://github.com/taco-group/stamp

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STAMP: Scalable Task And Model-agnostic Collaborative Perception

https://github.com/taeckyung/SoTTA

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SoTTA: Robust Test-Time Adaptation on Noisy Data Streams

https://github.com/taesikgong/note

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NOTE: Robust Continual Test-time Adaptation Against Temporal Correlation

https://github.com/taghikhah/quantod

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Quantile-based Maximum Likelihood Training for Outlier Detection

https://github.com/talk2car/Talk2Car

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A Baseline for the Commands For Autonomous Vehicles Challenge

https://github.com/tamirshor7/ears_code

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Active propulsion noise shaping for multi-rotor aircraft localization

https://github.com/tamu-edu-students/hypertools

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Real-Time Semantic Segmentation using Hyperspectral Images for Mapping Unstructured and Unknown Environments

https://github.com/tanvirnwu/trifuse

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LoLI-Street: Benchmarking Low-Light Image Enhancement and Beyond

https://github.com/tarashakhurana/emergent-occ-forecasting

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Differentiable Raycasting for Self-supervised Occupancy Forecasting

https://github.com/tasl-lab/uniocc

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UniOcc: A Unified Benchmark for Occupancy Forecasting and Prediction in Autonomous Driving

https://github.com/taveraantonio/pixda

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Pixel-by-Pixel Cross-Domain Alignment for Few-Shot Semantic Segmentation

https://github.com/tb-ad/tb-bench-110k-250k

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TB-Bench: Training and Testing Multi-Modal AI for Understanding Spatio-Temporal Traffic Behaviors from Dashcam Images/Videos

https://github.com/tbenciolini/safe-and-non-conservative-trajectory-planning

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Safe and Non-Conservative Trajectory Planning for Autonomous Driving Handling Unanticipated Behaviors of Traffic Participants

https://github.com/tberriel/ovo

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Open-Vocabulary Online Semantic Mapping for SLAM

https://github.com/tchittesh/fovea

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FOVEA: Foveated Image Magnification for Autonomous Navigation

https://github.com/teganmaharaj/zoneout

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Generalizing in the Real World with Representation Learning

https://github.com/tejas-deo/safe-navigation-training-autonomous-vehicles-using-deep-reinforcement-learning-in-carla

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Safe Navigation: Training Autonomous Vehicles using Deep Reinforcement Learning in CARLA

https://github.com/temporalrobrisk/temporal-robustness-risk

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Temporal Robustness of Stochastic Signals

https://github.com/tensorflow/lingvo

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DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection

https://github.com/tensorflow/models/tree/master/research/vid2depth

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Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints

https://github.com/testingautomated-usi/DeepJanus

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Model-based Exploration of the Frontier of Behaviours for Deep Learning System Testing

https://github.com/testingautomated-usi/genbo

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Boundary State Generation for Testing and Improvement of Autonomous Driving Systems

https://github.com/testingautomated-usi/maxitwo

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Two is Better Than One: Digital Siblings to Improve Autonomous Driving Testing

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