GM CRUISE HOLDINGS LLC (20240282117). APPROXIMATELY-PAIRED SIMULATION-TO-REAL IMAGE TRANSLATION simplified abstract
Contents
- 1 APPROXIMATELY-PAIRED SIMULATION-TO-REAL IMAGE TRANSLATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 APPROXIMATELY-PAIRED SIMULATION-TO-REAL IMAGE TRANSLATION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Simulation-to-Real Image Translation
- 1.13 Original Abstract Submitted
APPROXIMATELY-PAIRED SIMULATION-TO-REAL IMAGE TRANSLATION
Organization Name
Inventor(s)
Ashish Shrivastava of San Jose CA (US)
Charles Yingjia Zhang of Ottawa (CA)
APPROXIMATELY-PAIRED SIMULATION-TO-REAL IMAGE TRANSLATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240282117 titled 'APPROXIMATELY-PAIRED SIMULATION-TO-REAL IMAGE TRANSLATION
Simplified Explanation
The patent application describes a method for translating simulated images to real images using a generative adversarial network (GAN) model.
- Receiving an image pair with a real image and a simulated image.
- Determining style differences between the simulated and real images.
- Training the GAN to generate a post-processed simulated image.
Key Features and Innovation
- Method for translating simulated images to real images.
- Utilizes a style encoder to determine style differences.
- Trains a GAN to generate post-processed images.
Potential Applications
- Image editing and enhancement.
- Virtual reality and augmented reality applications.
- Gaming graphics development.
Problems Solved
- Improves the quality and realism of simulated images.
- Streamlines the process of translating simulated images to real images.
Benefits
- Enhances visual quality in various applications.
- Increases efficiency in image translation processes.
Commercial Applications
- "Facilitating approximately-paired simulation-to-real image translation" technology can be used in industries such as entertainment, design, and virtual reality development to enhance visual content and streamline image translation processes.
Prior Art
There may be prior art related to image translation methods using GAN models and style encoders that could provide additional insights into this technology.
Frequently Updated Research
Researchers are constantly exploring new techniques and improvements in image translation using GAN models, which could impact the development of this technology.
Questions about Simulation-to-Real Image Translation
How does this technology improve the quality of simulated images?
This technology improves the quality of simulated images by using a GAN model to generate post-processed images that closely resemble real images, enhancing visual realism and detail.
What are the potential applications of this image translation method beyond entertainment and gaming?
This image translation method can also be applied in fields such as medical imaging, satellite imagery analysis, and industrial design to enhance image quality and facilitate data analysis.
Original Abstract Submitted
disclosed are embodiments for facilitating approximately-paired simulation-to-real image translation. in some aspects, a method includes receiving, by a processing device performing training on a model, an approximately-paired image pair comprising a real image and a simulated image, wherein the simulated image is generated from the real image using contextual data of the real image; determining, by the processing device using a style encoder of the model, a style difference between a first style vector of the simulated image and a second style vector of the real image, wherein the first style vector and the second style vector encode style features of the simulated image and the real image using a style encoder; and inputting the style difference and the simulated image to a generative adversarial network (gan) of the model to train the gan to generate a post-processed simulated image.
