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/ddfan/balsa

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Bayesian Learning-Based Adaptive Control for Safety Critical Systems

https://github.com/decenter2021/saffron

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Feedback-feedforward Signal Control with Exogenous Demand Estimation in Congested Urban Road Networks

https://github.com/decisionforce/mmTransformer

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Multimodal Motion Prediction with Stacked Transformers

https://github.com/decisionforce/pgdrive

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Improving the Generalization of End-to-End Driving through Procedural Generation

https://github.com/decisionforce/pgdrive-generalization-paper

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Improving the Generalization of End-to-End Driving through Procedural Generation

https://github.com/deepcar/taillight_recognition

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Nighttime Driver Behavior Prediction Using Taillight Signal Recognition via CNN-SVM Classifier

https://github.com/deepmind/dm_hamiltonian_dynamics_suite

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Which priors matter? Benchmarking models for learning latent dynamics

https://github.com/deepmind/streetlearn

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Learning to Navigate in Cities Without a Map

https://github.com/deeprobust/DeepRobust

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Understanding Local Robustness of Deep Neural Networks under Natural Variations

https://github.com/deib-polimi/dillema

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DILLEMA: Diffusion and Large Language Models for Multi-Modal Augmentation

https://github.com/denyingmxd/CVCDepth

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Towards Cross-View-Consistent Self-Supervised Surround Depth Estimation

https://github.com/dependable-ai/nn-dependability-kit

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nn-dependability-kit: Engineering Neural Networks for Safety-Critical Autonomous Driving Systems

https://github.com/dependable-intelligent-systems-lab/xwhy

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Explainability of Point Cloud Neural Networks Using SMILE: Statistical Model-Agnostic Interpretability with Local Explanations

https://github.com/derekmei233/MissLight

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Reinforcement Learning Approaches for Traffic Signal Control under Missing Data

https://github.com/derrickxunu/cobevt

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CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformers

https://github.com/detectRecog/ZoomNet

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ZoomNet: Part-Aware Adaptive Zooming Neural Network for 3D Object Detection

https://github.com/devvansh1997/bgvp

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Comparison Of Deep Object Detectors On A New Vulnerable Pedestrian Dataset

https://github.com/df-boy/t-corresnet

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T-CorresNet: Template Guided 3D Point Cloud Completion with Correspondence Pooling Query Generation Strategy

https://github.com/dg-cavs/dg-coperception

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Towards Full-scene Domain Generalization in Multi-agent Collaborative Bird's Eye View Segmentation for Connected and Autonomous Driving

https://github.com/dgist-cvlab/flow4d

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Flow4D: Leveraging 4D Voxel Network for LiDAR Scene Flow Estimation

https://github.com/dhernandez0/sgm

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Embedded real-time stereo estimation via Semi-Global Matching on the GPU

https://github.com/dhu-mmct/dhu-mmct

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Towards Effective Multi-Moving-Camera Tracking: A New Dataset and Lightweight Link Model

https://github.com/digiamm/ba_md_slam

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Photometric LiDAR and RGB-D Bundle Adjustment

https://github.com/dimonenka/rl_policy_budget

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Personalized Reinforcement Learning with a Budget of Policies

https://github.com/dimvlachogiannis/humanlight

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HumanLight: Incentivizing Ridesharing via Human-centric Deep Reinforcement Learning in Traffic Signal Control

https://github.com/dinggh0817/4d_radar_mot

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Which Framework is Suitable for Online 3D Multi-Object Tracking for Autonomous Driving with Automotive 4D Imaging Radar?

https://github.com/dingmike001/saliendet-open-detection

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SalienDet: A Saliency-based Feature Enhancement Algorithm for Object Detection for Autonomous Driving

https://github.com/dingmyu/doubly-robust-self-training

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Doubly Robust Self-Training

https://github.com/dingpx/eai

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Expressive Forecasting of 3D Whole-body Human Motions

https://github.com/dipkamal/pasa

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PASA: Attack Agnostic Unsupervised Adversarial Detection using Prediction & Attribution Sensitivity Analysis

https://github.com/dlr-mi/utrack

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UTrack: Multi-Object Tracking with Uncertain Detections

https://github.com/dlr-rm/umf

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Unifying Local and Global Multimodal Features for Place Recognition in Aliased and Low-Texture Environments

https://github.com/dmn-sjk/ar-tta

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AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation

https://github.com/dmu-xmu/dsr

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Intrinsic Dynamics-Driven Generalizable Scene Representations for Vision-Oriented Decision-Making Applications

https://github.com/dmu-xmu/sar

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Sequential Action-Induced Invariant Representation for Reinforcement Learning

https://github.com/dmytrozabolotnii/autoware_mini

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Pedestrian motion prediction evaluation for urban autonomous driving

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