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/caipeide/VTGNet

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VTGNet: A Vision-based Trajectory Generation Network for Autonomous Vehicles in Urban Environments

https://github.com/caixxuan/vcat

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VCAT: Vulnerability-aware and Curiosity-driven Adversarial Training for Enhancing Autonomous Vehicle Robustness

https://github.com/caiyancheng/bfda

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Rethinking Cross-Domain Pedestrian Detection: A Background-Focused Distribution Alignment Framework for Instance-Free One-Stage Detectors

https://github.com/caizhongang/waymo_kitti_converter

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Leveraging Temporal Information for 3D Detection and Domain Adaptation

https://github.com/calvintanama/qd-driver-activity-reco

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Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained Environments

https://github.com/camera-culture/nlos-aided-autonomous-navigation

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Enhancing Autonomous Navigation by Imaging Hidden Objects using Single-Photon LiDAR

https://github.com/cancaries/SceneCrafter

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Unraveling the Effects of Synthetic Data on End-to-End Autonomous Driving

https://github.com/caopulan/Mask2Former-LT

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Frequency-based Matcher for Long-tailed Semantic Segmentation

https://github.com/cap-ntu/baconian-project

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Baconian: A Unified Open-source Framework for Model-Based Reinforcement Learning

https://github.com/caposerenity/daps

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Domain Adaptive Person Search

https://github.com/cardwing/Codes-for-IntRA-KD

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Inter-Region Affinity Distillation for Road Marking Segmentation

https://github.com/cardwing/Codes-for-Lane-Detection

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Learning Lightweight Lane Detection CNNs by Self Attention Distillation

https://github.com/carlinds/splatad

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SplatAD: Real-Time Lidar and Camera Rendering with 3D Gaussian Splatting for Autonomous Driving

https://github.com/carljohanhoel/BayesianRLForAutonomousDriving

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Tactical Decision-Making in Autonomous Driving by Reinforcement Learning with Uncertainty Estimation

https://github.com/carljohanhoel/EnsembleQuantileNetworks

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Ensemble Quantile Networks: Uncertainty-Aware Reinforcement Learning with Applications in Autonomous Driving

https://github.com/carolinewang01/naht

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N-Agent Ad Hoc Teamwork

https://github.com/carranza96/waymo-detection-optimization

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Enhancing Object Detection for Autonomous Driving by Optimizing Anchor Generation and Addressing Class Imbalance

https://github.com/carrotsniper/bp-sgcn

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BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction

https://github.com/cas-aisafetybasicresearchgroup/causaldiff

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CausalDiff: Causality-Inspired Disentanglement via Diffusion Model for Adversarial Defense

https://github.com/cathywu/flow

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Flow: A Modular Learning Framework for Mixed Autonomy Traffic

https://github.com/catonetwo/collaborative-perception-in-autonomous-driving

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Collaborative Perception in Autonomous Driving: Methods, Datasets and Challenges

https://github.com/cav-research-lab/safe-reinforcement-learning-using-symbolic-logical-programming-for-autonomous-highway-driving

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Towards Safe Autonomous Driving Policies using a Neuro-Symbolic Deep Reinforcement Learning Approach

https://github.com/cavalli1234/nefsac

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NeFSAC: Neurally Filtered Minimal Samples

https://github.com/cdb342/alocc

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ALOcc: Adaptive Lifting-based 3D Semantic Occupancy and Cost Volume-based Flow Prediction

https://github.com/cea-list/alpi

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ALPI: Auto-Labeller with Proxy Injection for 3D Object Detection using 2D Labels Only

https://github.com/cea-list/monoprob

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MonoProb: Self-Supervised Monocular Depth Estimation with Interpretable Uncertainty

https://github.com/cfzd/Ultra-Fast-Lane-Detection

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Ultra Fast Structure-aware Deep Lane Detection

https://github.com/cfzd/ultra-fast-lane-detection-v2

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Ultra Fast Deep Lane Detection with Hybrid Anchor Driven Ordinal Classification

https://github.com/cfzd/uniformer

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UniFusion: Unified Multi-view Fusion Transformer for Spatial-Temporal Representation in Bird's-Eye-View

https://github.com/cfzd/unifusion

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UniFusion: Unified Multi-view Fusion Transformer for Spatial-Temporal Representation in Bird's-Eye-View

https://github.com/cgchrfchscyrh/MixedTrafficControl

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Large-Scale Mixed-Traffic and Intersection Control using Multi-agent Reinforcement Learning

https://github.com/cgcl-codes/numbod

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NumbOD: A Spatial-Frequency Fusion Attack Against Object Detectors

https://github.com/ch-sa/labelCloud

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labelCloud: A Lightweight Domain-Independent Labeling Tool for 3D Object Detection in Point Clouds

https://github.com/changhao-chen/deep-learning-localization-mapping

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A Survey on Deep Learning for Localization and Mapping: Towards the Age of Spatial Machine Intelligence

https://github.com/charlesjin/synthetic_data

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Towards Context-Agnostic Learning Using Synthetic Data

https://github.com/charliesong1999/flashdreamer

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Enhancing Monocular 3D Scene Completion with Diffusion Model

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