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>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://bitbucket.org/fafz/bayesian-icp
공식 코드Speeding Up Iterative Closest Point Using Stochastic Gradient Descent
https://bitbucket.org/fafz/stein-icp
공식 코드Stein ICP for Uncertainty Estimation in Point Cloud Matching
https://git.iese.fraunhofer.de/scue/uncertaintyestimator/
공식 코드https://git.uwaterloo.ca/a9sarkar/traffic_behavior_modeling
공식 코드https://github.com/011235813/cm3
공식 코드CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning
https://github.com/1989Ryan/Semantic_SLAM
공식 코드Visual Semantic SLAM with Landmarks for Large-Scale Outdoor Environment
https://github.com/1uciusy/mcrl4or
공식 코드MCRL4OR: Multimodal Contrastive Representation Learning for Off-Road Environmental Perception
https://github.com/2019chengong/offline_rl_poisoner
공식 코드BAFFLE: Hiding Backdoors in Offline Reinforcement Learning Datasets
https://github.com/343gltysprk/ovow
공식 코드From Open Vocabulary to Open World: Teaching Vision Language Models to Detect Novel Objects
https://github.com/3dperceptionlab/toad
공식 코드https://github.com/3lis/rnn_vae
공식 코드On the Road with 16 Neurons: Mental Imagery with Bio-inspired Deep Neural Networks
https://github.com/4dvlab/stcrowd
공식 코드STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes
https://github.com/4dvlab/wildrefer
공식 코드https://github.com/7uheng/occood
공식 코드https://github.com/983632847/WebUAV-3M
공식 코드https://github.com/983632847/awesome-multimodal-object-tracking
공식 코드https://github.com/AHupuJR/RFNet
공식 코드https://github.com/AI-secure/Provable-Training-and-Verification-Approaches-Towards-Robust-Neural-Networks
공식 코드https://github.com/AI-secure/VeriGauge
공식 코드https://github.com/AIGeeksGroup/PedDet
공식 코드PedDet: Adaptive Spectral Optimization for Multimodal Pedestrian Detection
https://github.com/AIR-DISCOVER/Driving-Evaluation-Dataset
공식 코드A Comprehensive LLM-powered Framework for Driving Intelligence Evaluation
https://github.com/AIR-DISCOVER/Driving-Intellenge-Evaluation-Framework
공식 코드A Comprehensive LLM-powered Framework for Driving Intelligence Evaluation
https://github.com/AIR-DISCOVER/FreeAD
공식 코드https://github.com/ASU-APG/Targeted-Physical-Adversarial-Attacks-on-AD
공식 코드Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual Patterns
https://github.com/AbanobSoliman/IBISCape
공식 코드https://github.com/Abeni18/Deep-LSTM-for-Driver-Identification-
공식 코드Driver Identification Based on Vehicle Telematics Data using LSTM-Recurrent Neural Network
https://github.com/AdaCompNUS/GAMMA
공식 코드https://github.com/AdaCompNUS/despot
공식 코드https://github.com/AdvAttack/RoadSignAttack
공식 코드Targeted Physical-World Attention Attack on Deep Learning Models in Road Sign Recognition
https://github.com/Aegis1863/MacLight
공식 코드MacLight: Multi-scene Aggregation Convolutional Learning for Traffic Signal Control
https://github.com/Agricultural-Robotics-Bonn/visual-multi-crop-row-navigation
공식 코드Towards Autonomous Crop-Agnostic Visual Navigation in Arable Fields
https://github.com/Alejandro-Galan/Global-PC-Large-Transformations-Registration
공식 코드Global Point Cloud Registration Network for Large Transformations
https://github.com/AlejandroBarrera/birdnet2
공식 코드BirdNet+: End-to-End 3D Object Detection in LiDAR Bird's Eye View
https://github.com/AlexS28/SABER
공식 코드SABER: Data-Driven Motion Planner for Autonomously Navigating Heterogeneous Robots
https://github.com/AmirhoseinCh/DynamicPatch
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.