Yan et al., 2024 - Google Patents
OASim: an Open and Adaptive Simulator based on Neural Rendering for Autonomous DrivingYan et al., 2024
View PDF- Document ID
- 3349884082343952552
- Author
- Yan G
- Pi J
- Guo J
- Luo Z
- Dou M
- Deng N
- Huang Q
- Fu D
- Wen L
- Cai P
- Gao X
- Cai X
- Zhang B
- Yang X
- Bai Y
- Zhou H
- Shi B
- Publication year
- Publication venue
- arXiv preprint arXiv:2402.03830
External Links
Snippet
With deep learning and computer vision technology development, autonomous driving provides new solutions to improve traffic safety and efficiency. The importance of building high-quality datasets is self-evident, especially with the rise of end-to-end autonomous …
- 238000009877 rendering 0 title abstract description 32
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/10—Geometric effects
- G06T15/20—Perspective computation
- G06T15/205—Image-based rendering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T13/00—Animation
- G06T13/20—3D [Three Dimensional] animation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2200/00—Indexing scheme for image data processing or generation, in general
- G06T2200/24—Indexing scheme for image data processing or generation, in general involving graphical user interfaces [GUIs]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T19/00—Manipulating 3D models or images for computer graphics
- G06T19/006—Mixed reality
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2219/00—Indexing scheme for manipulating 3D models or images for computer graphics
- G06T2219/20—Indexing scheme for editing of 3D models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2210/00—Indexing scheme for image generation or computer graphics
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Wu et al. | Mars: An instance-aware, modular and realistic simulator for autonomous driving | |
Fang et al. | Augmented LiDAR simulator for autonomous driving | |
Lin et al. | Capturing, reconstructing, and simulating: the urbanscene3d dataset | |
US10643106B2 (en) | System and method for procedurally synthesizing datasets of objects of interest for training machine-learning models | |
Zhao et al. | Drivedreamer-2: Llm-enhanced world models for diverse driving video generation | |
Alvey et al. | Simulated photorealistic deep learning framework and workflows to accelerate computer vision and unmanned aerial vehicle research | |
Mo et al. | Terra: A smart and sensible digital twin framework for robust robot deployment in challenging environments | |
Yu et al. | Autonomous vehicles digital twin: A practical paradigm for autonomous driving system development | |
Wang et al. | A synthetic dataset for Visual SLAM evaluation | |
Li et al. | The paralleleye-cs dataset: Constructing artificial scenes for evaluating the visual intelligence of intelligent vehicles | |
CN115186473A (en) | Scene perception modeling and verifying method based on parallel intelligence | |
Yang et al. | Recovering and simulating pedestrians in the wild | |
Li et al. | Multi-modal neural feature fusion for automatic driving through perception-aware path planning | |
Yang et al. | Drivearena: A closed-loop generative simulation platform for autonomous driving | |
Wang et al. | NeRF in Robotics: A Survey | |
He et al. | Neural Radiance Field in Autonomous Driving: A Survey | |
Yan et al. | OASim: an Open and Adaptive Simulator based on Neural Rendering for Autonomous Driving | |
Vukić et al. | Unity based urban environment simulation for autonomous vehicle stereo vision evaluation | |
Rivalcoba et al. | Towards urban crowd visualization | |
Serdel et al. | SMaNa: Semantic Mapping and Navigation Architecture for Autonomous Robots. | |
Benčević et al. | Tool for automatic labeling of objects in images obtained from Carla autonomous driving simulator | |
Lindén et al. | Enhancing drone surveillance with NeRF: Real-world applications and simulated environments | |
Wang et al. | Safely Test Autonomous Vehicles with Augmented Reality | |
Li et al. | SyntheOcc: Synthesize Geometric-Controlled Street View Images through 3D Semantic MPIs | |
Liu et al. | PA-Net: Plane Attention Network for real-time urban scene reconstruction |