Papers with Code 아카이브
Autonomous Vehicles
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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>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Test-time Correction: An Online 3D Detection System via Visual Prompting
Aligned Delta-Triplane Transformers as Occupancy World Models
GEMINUS: Dual-aware Global and Scene-Adaptive Mixture-of-Experts for End-to-End Autonomous Driving
AGENTS-LLM: Augmentative GENeration of Challenging Traffic Scenarios with an Agentic LLM Framework
World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving
LaViPlan : Language-Guided Visual Path Planning with RLVR
Channel-wise Motion Features for Efficient Motion Segmentation
Orbis: Overcoming Challenges of Long-Horizon Prediction in Driving World Models
Evaluating Reinforcement Learning Algorithms for Navigation in Simulated Robotic Quadrupeds: A Comparative Study Inspired by Guide Dog Behaviour
Towards Autonomous Riding: A Review of Perception, Planning, and Control in Intelligent Two-Wheelers
Vision-based Perception for Autonomous Vehicles in Obstacle Avoidance Scenarios
Safeguarding Federated Learning-based Road Condition Classification
GeoDistill: Geometry-Guided Self-Distillation for Weakly Supervised Cross-View Localization
A Survey on Interpretability in Visual Recognition
Towards Depth Foundation Model: Recent Trends in Vision-Based Depth Estimation
3DGAA: Realistic and Robust 3D Gaussian-based Adversarial Attack for Autonomous Driving
LifelongPR: Lifelong knowledge fusion for point cloud place recognition based on replay and prompt learning
Scene-Aware Conversational ADAS with Generative AI for Real-Time Driver Assistance
$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting
Review of Feed-forward 3D Reconstruction: From DUSt3R to VGGT
Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection
Objectomaly: Objectness-Aware Refinement for OoD Segmentation with Structural Consistency and Boundary Precision
ILNet: Trajectory Prediction with Inverse Learning Attention for Enhancing Intention Capture
A Neural Representation Framework with LLM-Driven Spatial Reasoning for Open-Vocabulary 3D Visual Grounding
3DGS_LSR:Large_Scale Relocation for Autonomous Driving Based on 3D Gaussian Splatting
LeAD: The LLM Enhanced Planning System Converged with End-to-end Autonomous Driving
Towards Solar Altitude Guided Scene Illumination
TigAug: Data Augmentation for Testing Traffic Light Detection in Autonomous Driving Systems
MCAM: Multimodal Causal Analysis Model for Ego-Vehicle-Level Driving Video Understanding
Fast and Accurate Collision Probability Estimation for Autonomous Vehicles using Adaptive Sigma-Point Sampling
Simultaneous Localization and Mapping Using Active mmWave Sensing in 5G NR
Robustifying 3D Perception through Least-Squares Multi-Agent Graphs Object Tracking
Beyond One Shot, Beyond One Perspective: Cross-View and Long-Horizon Distillation for Better LiDAR Representations
YOLO-APD: Enhancing YOLOv8 for Robust Pedestrian Detection on Complex Road Geometries
NRSeg: Noise-Resilient Learning for BEV Semantic Segmentation via Driving World Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.