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/rose-stl-lab/pecco

공식 코드

Probabilistic Symmetry for Multi-Agent Dynamics

https://github.com/rosewang2008/rmaddpg

공식 코드

R-MADDPG for Partially Observable Environments and Limited Communication

https://github.com/rossgreer/doscenes

공식 코드

doScenes: An Autonomous Driving Dataset with Natural Language Instruction for Human Interaction and Vision-Language Navigation

https://github.com/rovislab/loopdb

공식 코드

LoopDB: A Loop Closure Dataset for Large Scale Simultaneous Localization and Mapping

https://github.com/rpl-cmu/bevloc

공식 코드

BEVLoc: Cross-View Localization and Matching via Birds-Eye-View Synthesis

https://github.com/rruisong/fedbevt

공식 코드

FedBEVT: Federated Learning Bird's Eye View Perception Transformer in Road Traffic Systems

https://github.com/rruisong/h2-fed

공식 코드

Federated Learning Framework Coping with Hierarchical Heterogeneity in Cooperative ITS

https://github.com/rsinghlab/ovo

공식 코드

One-Versus-Others Attention: Scalable Multimodal Integration for Biomedical Data

https://github.com/rst-tu-dortmund/diff_epo_planner

공식 코드

Energy-based Potential Games for Joint Motion Forecasting and Control

https://github.com/rst-tu-dortmund/lord

공식 코드

LoRD: Adapting Differentiable Driving Policies to Distribution Shifts

https://github.com/rstless-research/ncod-learning-with-noisy-labels

공식 코드

Learning with Noisy Labels through Learnable Weighting and Centroid Similarity

https://github.com/ruanyudi/ecaformer

공식 코드

ECAFormer: Low-light Image Enhancement using Cross Attention

https://github.com/rubbish001/co-fix3d

공식 코드

Co-Fix3D: Enhancing 3D Object Detection with Collaborative Refinement

https://github.com/rui-qian/SoTA-3D-Object-Detection

공식 코드

3D Object Detection for Autonomous Driving: A Survey

https://github.com/ruili3/dynamic-multiframe-depth

공식 코드

Learning to Fuse Monocular and Multi-view Cues for Multi-frame Depth Estimation in Dynamic Scenes

https://github.com/ruipingl/miss

공식 코드

Fourier Prompt Tuning for Modality-Incomplete Scene Segmentation

https://github.com/ruipingl/skr_pea

공식 코드

TransKD: Transformer Knowledge Distillation for Efficient Semantic Segmentation

https://github.com/ruipingl/transkd

공식 코드

TransKD: Transformer Knowledge Distillation for Efficient Semantic Segmentation

https://github.com/ruiyum/stone

공식 코드

STONE: A Submodular Optimization Framework for Active 3D Object Detection

https://github.com/runjian-chen/co3

공식 코드

CO^3: Cooperative Unsupervised 3D Representation Learning for Autonomous Driving

https://github.com/runkaizhao/liladet

공식 코드

Advancements in 3D Lane Detection Using LiDAR Point Clouds: From Data Collection to Model Development

https://github.com/runpeidong/pointdistiller

공식 코드

PointDistiller: Structured Knowledge Distillation Towards Efficient and Compact 3D Detection

https://github.com/ruyakrgl/SPL-WSTL

공식 코드

A Safe Preference Learning Approach for Personalization with Applications to Autonomous Vehicles

https://github.com/rvp-group/vbr-devkit

공식 코드

VBR: A Vision Benchmark in Rome

https://github.com/rwightman/pytorch-image-models

공식 코드

EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction

https://github.com/s7desai/ped-mapping

공식 코드

Pedestrian Behavior Maps for Safety Advisories: CHAMP Framework and Real-World Data Analysis

https://github.com/saadejazz/mpc-trust-cbf

공식 코드

Trust-aware Safe Control for Autonomous Navigation: Estimation of System-to-human Trust for Trust-adaptive Control Barrier Functions

https://github.com/saadejazz/smato

공식 코드

Trust-aware Safe Control for Autonomous Navigation: Estimation of System-to-human Trust for Trust-adaptive Control Barrier Functions

https://github.com/saadejazz/trusty

공식 코드

Trust-aware Safe Control for Autonomous Navigation: Estimation of System-to-human Trust for Trust-adaptive Control Barrier Functions

https://github.com/saba99/classifying-objects-3d-point-clouds

공식 코드

Classifying Objects in 3D Point Clouds Using Recurrent Neural Network: A GRU LSTM Hybrid Approach

https://github.com/safednn-group/nap-ood

공식 코드

Detection of out-of-distribution samples using binary neuron activation patterns

https://github.com/safednn-group/naptron

공식 코드

Detecting Out-of-distribution Objects Using Neuron Activation Patterns

https://github.com/saferl-lab/safe-marl-in-autonomous-driving

공식 코드

Safe Multi-Agent Reinforcement Learning with Bilevel Optimization in Autonomous Driving

https://github.com/saferoboticslab/dual_control_hri

공식 코드

Active Uncertainty Reduction for Safe and Efficient Interaction Planning: A Shielding-Aware Dual Control Approach

https://github.com/safreita1/unmask

공식 코드

UnMask: Adversarial Detection and Defense Through Robust Feature Alignment

https://github.com/sainingzhang/uc-gs

공식 코드

Drone-assisted Road Gaussian Splatting with Cross-view Uncertainty

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