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/core-robotics-lab/icct

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Learning Interpretable, High-Performing Policies for Autonomous Driving

https://github.com/core-robotics-lab/opponent-modeling

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Diffusion-Reinforcement Learning Hierarchical Motion Planning in Multi-agent Adversarial Games

https://github.com/core9724/awesome-lane-detection

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Monocular Lane Detection Based on Deep Learning: A Survey

https://github.com/coslab-kr/tinyseg

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TinySeg: Model Optimizing Framework for Image Segmentation on Tiny Embedded Systems

https://github.com/cps-il/verifiable-od

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Verifiable Obstacle Detection

https://github.com/craigiedon/commonrules

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Adaptive Splitting of Reusable Temporal Monitors for Rare Traffic Violations

https://github.com/cram3r95/mapfe4mp

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Exploring Map-based Features for Efficient Attention-based Vehicle Motion Prediction

https://github.com/crepuscularlight/semanticloopclosure

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LiDAR Loop Closure Detection using Semantic Graphs with Graph Attention Networks

https://github.com/cristianocapone/biodreaming

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Towards biologically plausible Dreaming and Planning in recurrent spiking networks

https://github.com/crowdbotp/OpenTraj

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OpenTraj: Assessing Prediction Complexity in Human Trajectories Datasets

https://github.com/crunchbang/MP_Project

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Vehicle Driving Assistant

https://github.com/csimo005/summit

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SUMMIT: Source-Free Adaptation of Uni-Modal Models to Multi-Modal Targets

https://github.com/csiro-robotics/LoGG3D-Net

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LoGG3D-Net: Locally Guided Global Descriptor Learning for 3D Place Recognition

https://github.com/csjfwang/forecast-peft

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Forecast-PEFT: Parameter-Efficient Fine-Tuning for Pre-trained Motion Forecasting Models

https://github.com/cskkxjk/vampire

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Regulating Intermediate 3D Features for Vision-Centric Autonomous Driving

https://github.com/cts198859/deeprl_network

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Multi-agent Reinforcement Learning for Networked System Control

https://github.com/cts198859/deeprl_signal_control

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Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control

https://github.com/ctu-mrs/flight_forge

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FlightForge: Advancing UAV Research with Procedural Generation of High-Fidelity Simulation and Integrated Autonomy

https://github.com/ctu-vras/t-concord3d

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Teachers in concordance for pseudo-labeling of 3D sequential data

https://github.com/cuge1995/u6da

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Adversarial samples for deep monocular 6D object pose estimation

https://github.com/cuiyx1720/awesome-cot4ad

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Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects

https://github.com/cure-lab/contranet

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What You See is Not What the Network Infers: Detecting Adversarial Examples Based on Semantic Contradiction

https://github.com/cuzaoo/sanet-main

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Spatial-Assistant Encoder-Decoder Network for Real Time Semantic Segmentation

https://github.com/cv4ra/sota-place-recognitioner

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Place Recognition: A Comprehensive Review, Current Challenges and Future Directions

https://github.com/cvg/nice-slam

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NICE-SLAM: Neural Implicit Scalable Encoding for SLAM

https://github.com/cvlab-unibo/d4-dbst

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Plugging Self-Supervised Monocular Depth into Unsupervised Domain Adaptation for Semantic Segmentation

https://github.com/cvlab-unibo/mm2d3d

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Exploiting the Complementarity of 2D and 3D Networks to Address Domain-Shift in 3D Semantic Segmentation

https://github.com/cvml-cfu/ecam

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ECAM: A Contrastive Learning Approach to Avoid Environmental Collision in Trajectory Forecasting

https://github.com/cxliu0314/colmdriver

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CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving

https://github.com/cxy1997/3D_adapt_auto_driving

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Train in Germany, Test in The USA: Making 3D Object Detectors Generalize

https://github.com/cxy1997/DiffuBox

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DiffuBox: Refining 3D Object Detection with Point Diffusion

https://github.com/cybonic/attdlnet

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AttDLNet: Attention-based DL Network for 3D LiDAR Place Recognition

https://github.com/cybonic/orchnet

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ORCHNet: A Robust Global Feature Aggregation approach for 3D LiDAR-based Place recognition in Orchards

https://github.com/cyprienquemeneur/fedpylot

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FedPylot: Navigating Federated Learning for Real-Time Object Detection in Internet of Vehicles

https://github.com/czming/RONELD-Lane-Detection

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RONELD: Robust Neural Network Output Enhancement for Active Lane Detection

https://github.com/d1024choi/pathgan_pytorch

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PathGAN: Local Path Planning with Attentive Generative Adversarial Networks

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