https://github.com/git-disl/TOG
공식 코드TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems
Papers with Code 아카이브
Autonomous Driving
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 6
- 평가표
- 4
- 보존된 평가 기록
- 23
Autonomous driving is the task of driving a vehicle 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: 0.5">(Image credit: Exploring the Limitations of Behavior Cloning for Autonomous Driving)</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/gmum/make-interval-bound-propagation-great-again
공식 코드https://github.com/goodarzmehr/simbev
공식 코드SimBEV: A Synthetic Multi-Task Multi-Sensor Driving Data Generation Tool and Dataset
https://github.com/google-research/causal-agents
공식 코드CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal Relationships
https://github.com/google/next-prediction
공식 코드Peeking into the Future: Predicting Future Person Activities and Locations in Videos
https://github.com/gorilla-lab-scut/vista
공식 코드VISTA: Boosting 3D Object Detection via Dual Cross-VIew SpaTial Attention
https://github.com/gorkaydemir/FTGN
공식 코드https://github.com/grandzxw/triplemixer
공식 코드TripleMixer: A 3D Point Cloud Denoising Model for Adverse Weather
https://github.com/gt-arc/apr-transformer
공식 코드https://github.com/gtzly/FADNet
공식 코드Monocular 3D Object Detection with Sequential Feature Association and Depth Hint Augmentation
https://github.com/guangjinpan/lwlm
공식 코드Large Wireless Localization Model (LWLM): A Foundation Model for Positioning in 6G Networks
https://github.com/guangmingw/DOPlearning
공식 코드Unsupervised Learning of Depth, Optical Flow and Pose with Occlusion from 3D Geometry
https://github.com/gugarosa/synthetic_rbms
공식 코드Fast Ensemble Learning Using Adversarially-Generated Restricted Boltzmann Machines
https://github.com/guiliang/cirl-benchmarks-public
공식 코드Benchmarking Constraint Inference in Inverse Reinforcement Learning
https://github.com/guiliang/icrl-benchmarks-public
공식 코드Benchmarking Constraint Inference in Inverse Reinforcement Learning
https://github.com/gujiaqivadin/HomographyLoss
공식 코드https://github.com/gurkirt/3D-RetinaNet
공식 코드ROAD: The ROad event Awareness Dataset for Autonomous Driving
https://github.com/gurkirt/AMTNet
공식 코드https://github.com/gurkirt/road-dataset
공식 코드ROAD: The ROad event Awareness Dataset for Autonomous Driving
https://github.com/gustavokcouto/hgail
공식 코드https://github.com/guytenn/terminator
공식 코드https://github.com/gyyang23/rdrnet
공식 코드Reparameterizable Dual-Resolution Network for Real-time Semantic Segmentation
https://github.com/hai-chao-zhang/oostraj
공식 코드OOSTraj: Out-of-Sight Trajectory Prediction With Vision-Positioning Denoising
https://github.com/haibao-yu/ffnet-vic3d
공식 코드Vehicle-Infrastructure Cooperative 3D Object Detection via Feature Flow Prediction
https://github.com/haiyang-w/unitr
공식 코드UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation
https://github.com/hal-lucination/segfuse
공식 코드360 Depth Estimation in the Wild -- The Depth360 Dataset and the SegFuse Network
https://github.com/halajun/multimot_track
공식 코드https://github.com/hama-dl-dev/sesame
공식 코드SeSame: Simple, Easy 3D Object Detection with Point-Wise Semantics
https://github.com/hamedhaghighi/cls2r
공식 코드A Unified Generative Framework for Realistic Lidar Simulation in Autonomous Driving Systems
https://github.com/hamedhaghighi/coligen
공식 코드A Unified Generative Framework for Realistic Lidar Simulation in Autonomous Driving Systems
https://github.com/hanjianghu/pixel-wise-smoothing
공식 코드Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations
https://github.com/hanyangzhong/fenet
공식 코드https://github.com/hanymragab/navinst19
공식 코드Automotive Speed Estimation: Sensor Types and Error Characteristics from OBD-II to ADAS
https://github.com/haohao11/MCENET
공식 코드MCENET: Multi-Context Encoder Network for Homogeneous Agent Trajectory Prediction in Mixed Traffic
https://github.com/haomo-ai/cam4docc
공식 코드Cam4DOcc: Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications
https://github.com/haomo-ai/motionseg3d
공식 코드Efficient Spatial-Temporal Information Fusion for LiDAR-Based 3D Moving Object Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.