BEIJING, Aug. 7, 2023 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that its R&D team is working on algorithms for 3D image generation based on Generative Adversarial Networks. Generative Adversarial Network (GAN) is an effective model for generating data and creating intelligence. The basic GAN model consists structurally of a Generator and a Discriminator.The initial purpose of GAN is to perform unsupervised learning based on large amounts of unlabeled data, which has the ability to generate data in various forms (image, speech, language, etc.).
The algorithm generates realistic 3D images by means of adversarial training. The 3D generation of the generative adversarial network is achieved by adversarial training of a generator and a discriminator. The generator is responsible for generating realistic 3D models, while the discriminator is responsible for determining whether the 3D models generated by the generator are realistic or not. During the training process, the generator keeps generating 3D models and the discriminator keeps judging their realism until the 3D models generated by the generator cannot be distinguished by the discriminator, at which time the training of the generator is completed. The generator can generate different 3D models, thus realizing the diversity of 3D models.
The steps of 3D image generation for GAN mainly include:
Data preparation: prepare the 3D model dataset for training, which can be a real 3D model or a virtual 3D model.
Structure design: design the network structure of the generator and discriminator. The generator is responsible for generating realistic 3D models, and the discriminator is responsible for judging whether the 3D models generated by the generator are realistic or not.
Training the model: the generator and the discriminator are trained using the prepared dataset. In training, the generator keeps generating 3D models and the discriminator keeps judging their authenticity until the 3D models generated by the generator cannot be distinguished by the discriminator, at which point the training of the generator is completed.
Optimize the model: Use optimization algorithms to optimize the generated 3D model to make it more lifelike and realistic.
With the continuous "evolution" of the "generative adversarial network" technology, it has been expanded from the traditional computer vision to other directions, in the confrontation samples, data augmentation, migration learning and creation of intelligence, etc. have shown great potential, and has become a new trend of deep learning and artificial intelligence technology.
WiMi's 3D image generation algorithm based on generative adversarial networks has a wide range of applications and can provide important technical support for game development, virtual reality, architectural design and other fields. In game development, adversarial networks can be used to generate realistic 3D character models, scene models, etc., to enhance the realism and playability of the game. In virtual reality, the GAN can be used to generate realistic 3D scene models to enhance the immersion of virtual reality. In architectural design, it can be used to generate realistic 3D building models to help designers carry out architectural design and planning.
About WIMI Hologram Cloud
WIMI Hologram Cloud, Inc. (NASDAQ:WIMI) is a holographic cloud comprehensive technical solution provider that focuses on professional areas including holographic AR automotive HUD software, 3D holographic pulse LiDAR, head-mounted light field holographic equipment, holographic semiconductor, holographic cloud software, holographic car navigation and others. Its services and holographic AR technologies include holographic AR automotive application, 3D holographic pulse LiDAR technology, holographic vision semiconductor technology, holographic software development, holographic AR advertising technology, holographic AR entertainment technology, holographic ARSDK payment, interactive holographic communication and other holographic AR technologies.
Safe Harbor Statements
This press release contains "forward-looking statements" within the Private Securities Litigation Reform Act of 1995. These forward-looking statements can be identified by terminology such as "will," "expects," "anticipates," "future," "intends," "plans," "believes," "estimates," and similar statements. Statements that are not historical facts, including statements about the Company's beliefs and expectations, are forward-looking statements. Among other things, the business outlook and quotations from management in this press release and the Company's strategic and operational plans contain forward−looking statements. The Company may also make written or oral forward−looking statements in its periodic reports to the US Securities and Exchange Commission ("SEC") on Forms 20−F and 6−K, in its annual report to shareholders, in press releases, and other written materials, and in oral statements made by its officers, directors or employees to third parties. Forward-looking statements involve inherent risks and uncertainties. Several factors could cause actual results to differ materially from those contained in any forward−looking statement, including but not limited to the following: the Company's goals and strategies; the Company's future business development, financial condition, and results of operations; the expected growth of the AR holographic industry; and the Company's expectations regarding demand for and market acceptance of its products and services.
Further information regarding these and other risks is included in the Company's annual report on Form 20-F and the current report on Form 6-K and other documents filed with the SEC. All information provided in this press release is as of the date of this press release. The Company does not undertake any obligation to update any forward-looking statement except as required under applicable laws.