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/mrnabati/RRPN

공식 코드

RRPN: Radar Region Proposal Network for Object Detection in Autonomous Vehicles

https://github.com/mrottmann/MetaSeg

공식 코드

Detection of False Positive and False Negative Samples in Semantic Segmentation

https://github.com/msscao/acdepth

공식 코드

Always Clear Depth: Robust Monocular Depth Estimation under Adverse Weather

https://github.com/muhayyuddin/visual-servoing

공식 코드

Vision-Based Autonomous Navigation for Unmanned Surface Vessel in Extreme Marine Conditions

https://github.com/murpheylab/maxdiffrl

공식 코드

Maximum diffusion reinforcement learning

https://github.com/mustansarfiaz/ddam-ps

공식 코드

DDAM-PS: Diligent Domain Adaptive Mixer for Person Search

https://github.com/my-name-is-D/high_level_nav_planning

공식 코드

Learning Dynamic Cognitive Map with Autonomous Navigation

https://github.com/mystorm16/bsh-det3d

공식 코드

BSH-Det3D: Improving 3D Object Detection with BEV Shape Heatmap

https://github.com/nab170130/new_streamline

공식 코드

STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional Settings

https://github.com/nail-hnu/esvo2

공식 코드

ESVO2: Direct Visual-Inertial Odometry with Stereo Event Cameras

https://github.com/nailperry-zd/paddleseg-trianglenet

공식 코드

TriangleNet: Edge Prior Augmented Network for Semantic Segmentation through Cross-Task Consistency

https://github.com/nandantumu/conformal_region_designer

공식 코드

Multi-Modal Conformal Prediction Regions with Simple Structures by Optimizing Convex Shape Templates

https://github.com/naoe-5thlab/mmg-1p1r-simulator

공식 코드

Perspective on the Marine Simulator for Autonomous Vessel Development

https://github.com/naomiex/mdha

공식 코드

MDHA: Multi-Scale Deformable Transformer with Hybrid Anchors for Multi-View 3D Object Detection

https://github.com/naufalso/adversarial-manhole

공식 코드

Adversarial Manhole: Challenging Monocular Depth Estimation and Semantic Segmentation Models with Patch Attack

https://github.com/naver/kapture-localization

공식 코드

Benchmarking Image Retrieval for Visual Localization

https://github.com/navganti/SIVO

공식 코드

Network Uncertainty Informed Semantic Feature Selection for Visual SLAM

https://github.com/nazat28/xai-based-feature-ensemble-for-enhanced-anomaly-detection-in-autonomous-driving-systems

공식 코드

XAI-based Feature Ensemble for Enhanced Anomaly Detection in Autonomous Driving Systems

https://github.com/neeharperi/futuredet

공식 코드

Forecasting from LiDAR via Future Object Detection

https://github.com/neu-real/streammos

공식 코드

StreamMOS: Streaming Moving Object Segmentation with Multi-View Perception and Dual-Span Memory

https://github.com/neu-vi/odtformer

공식 코드

ODTFormer: Efficient Obstacle Detection and Tracking with Stereo Cameras Based on Transformer

https://github.com/neurai-lab/cude-monodepthcl

공식 코드

Continual Learning of Unsupervised Monocular Depth from Videos

https://github.com/neurai-lab/mimdepth

공식 코드

Image Masking for Robust Self-Supervised Monocular Depth Estimation

https://github.com/neurai-lab/mmc

공식 코드

Does Thermal data make the detection systems more reliable?

https://github.com/nexer8/se3d

공식 코드

SE3D: A Framework For Saliency Method Evaluation In 3D Imaging

https://github.com/nicholascg/glare_dataset

공식 코드

GLARE: A Dataset for Traffic Sign Detection in Sun Glare

https://github.com/nicholasli1995/pcp-mv

공식 코드

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection

https://github.com/nickstheisen/hyperseg

공식 코드

HS3-Bench: A Benchmark and Strong Baseline for Hyperspectral Semantic Segmentation in Driving Scenarios

https://github.com/nicolamarinello/offsetocc

공식 코드

Camera-Only 3D Panoptic Scene Completion for Autonomous Driving through Differentiable Object Shapes

https://github.com/nightmare-n/pvt-ssd

공식 코드

PVT-SSD: Single-Stage 3D Object Detector with Point-Voxel Transformer

https://github.com/nilakshdas/skelevision

공식 코드

SkeleVision: Towards Adversarial Resiliency of Person Tracking with Multi-Task Learning

https://github.com/nish03/FuseVis

공식 코드

FuseVis: Interpreting neural networks for image fusion using per-pixel saliency visualization

https://github.com/nish03/ffs

공식 코드

Normalizing Flow based Feature Synthesis for Outlier-Aware Object Detection

https://github.com/niveditarufus/CMSVG

공식 코드

Cosine meets Softmax: A tough-to-beat baseline for visual grounding

https://github.com/nkondapa/visualknowledgetracing

공식 코드

Visual Knowledge Tracing

https://github.com/nnanhuang/s3gaussian

공식 코드

$\textit{S}^3$Gaussian: Self-Supervised Street Gaussians for Autonomous Driving

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