WiMi to Work on Multi-Channel CNN-based 3D Object Detection Algorithm

Rhea-AI Summary

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) announced the development of a 3D object detection algorithm utilizing multi-channel convolutional neural networks (CNN). This innovative technology harnesses RGB, depth, and bird's-eye view (BEV) images to identify the object's category, 3D size, and spatial location with enhanced accuracy.

The algorithm processes point cloud data directly, improving feature extraction for 3D bounding boxes. It has significant application prospects in areas such as autonomous driving, intelligent robotics, and security monitoring, driven by advancements in data acquisition technology and deep learning.

WiMi positions itself as a leader in the holographic AR industry, focusing on various sectors including AR automotive applications and holographic software development.

Positive

• Development of a unique 3D object detection algorithm using multi-channel CNN technology.
• Increased accuracy and efficiency in object detection with applications in autonomous driving and intelligent robotics.
• Broad application potential across various industries including AR, remote sensing, and biomedical fields.

Negative

• None.

BEIJING, April 14, 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 a 3D object detection algorithm based on multi-channel convolutional neural networks. It uses RGB, depth, and BEV images as inputs to the network to regress the object's category, 3D size, and spatial location, respectively. The algorithm combines a multi-channel neural network system to achieve 3D object detection.

BEV images provide information perpendicular to the camera viewpoint and can represent the spatial distribution of objects. The BEV images are generated using point cloud projection and used as the neural network input to improve the 3D object detection accuracy. By directly processing the input point cloud data through CNN, the problem of encoding and feature extraction of disordered point clouds can be solved to obtain end-to-end regression of 3D bounding boxes. The algorithm extracts only 3D suggestion frames from monocular images and estimates 3D bounding boxes, then combines laser point clouds with visual information and projects the point clouds into the BEV images. The algorithm feeds the information into a CNN and fuses multiple pieces of information to estimate the 3D bounding box. The fusion of multiple information facilitates better detection of objects in 3D space.

WiMi's 3D object detection algorithm, which can simultaneously identify the category, spatial location, and 3D size of objects, dramatically improves the accuracy and efficiency of object detection. The multi-channel object detection neural network system allows 3D object detection, extending the input to RGB, depth, and BEV images. First, RGB image, depth image, and BEV image are used as the network input, and then the feature map is obtained by CNN. And the feature vector of the proposed region in the feature map is generated using a spatial pyramid pooling layer, and then the classification and position regression of the object is realized using a classifier and regressor. The classifier is mainly used to determine which class the extracted features in the proposal belong to. Finally, multi-task regression will be performed by two fully connected layers to predict object classes and 3D bounding boxes.

3D object detection and recognition have always been crucial technology in computer vision. It is the machine's basis for understanding and interacting with the outside world. 3D object detection technology can be widely applied in navigation, intelligent robotics, crewless vehicles, and security monitoring.

With the advancement of 3D data acquisition technology, the enhancement of computing power, deep learning, and the increase of application demand, the research and application of 3D vision technology have received more and more attention. WiMi's algorithm enjoys a broad application prospect in autonomous driving, intelligent robotics, ARVR, remote sensing, biomedical, and so on.

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.

 

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SOURCE WiMi Hologram Cloud Inc.

FAQ

What is the new algorithm announced by WiMi Hologram Cloud?

WiMi announced a 3D object detection algorithm developed using multi-channel convolutional neural networks, enhancing the accuracy of detecting object categories, sizes, and spatial locations.

What technology does WiMi's new algorithm utilize?

The algorithm utilizes RGB, depth, and bird's-eye view (BEV) images as inputs for improved 3D object detection.

What are the potential applications of WiMi's 3D object detection algorithm?

The algorithm has potential applications in autonomous driving, intelligent robotics, navigation, and security monitoring.

When was the announcement made by WiMi Hologram Cloud?

The announcement was made on April 14, 2023.

What is the stock symbol for WiMi Hologram Cloud?

The stock symbol for WiMi Hologram Cloud is WIMI.