The Global Vision Transformers Market size is expected to reach $2.1 billion by 2030, rising at a market growth of 36.5% CAGR during the forecast period.
Image captioning enriches the user experience across various industries, including e-commerce, social media, news, and entertainment. By providing meaningful and contextually relevant captions for images, ViTs improves user engagement and understanding. Therefore, the image captioning segment will capture 15.8% share in the market by 2030. Image captioning can generate personalized captions tailored to individual user preferences, creating a more engaging and interactive user experience. Image captions enhance the accuracy of visual search by associating keywords and context with images. This is particularly valuable in e-commerce, where consumers search for specific products. Some of the factors impacting the market are growing superior performance in computer vision, increasing adoption of transfer learning and pre-trained models, and high installation cost of these.
Vision transformers have demonstrated superior performance in various computer vision tasks, including object detection, image classification, and segmentation. Their ability to capture long-range dependencies and handle complex visual data sets them apart from traditional computer vision approaches, attracting interest from various industries. These are known for superior accuracy and precision in tasks like image classification, object detection, and image segmentation. Additionally, the availability of pre-trained vision transformer models, like ViT, DeiT, and swin transformer, makes it easier for developers to leverage these models for specific tasks. This accelerates the development of applications and reduces the time and resources required for model training. Pre-trained models are a starting point for many developers and organizations. Increasing adoption of transfer learning and pre-trained models has been a pivotal factor in driving the growth of the market.
However, training large ViT models, particularly for complex tasks, consumes a significant number of computational resources and time. Acquiring and sustaining these resources can be prohibitively expensive for businesses with low resources. Building and maintaining ViT models requires a skilled workforce with expertise in machine learning and deep learning. Hiring and training employees in this field can be costly and time-consuming. Deploying ViTs on edge devices, such as smartphones or IoT devices, may require additional investment in optimization to ensure efficient use of resources, which can be costly. High installation cost of these hinders the market’s growth.
Under solution type, the market is categorized into hardware and software. In 2022, the software segment witnessed the largest revenue share in the market. ViT software includes deep learning frameworks like TensorFlow, PyTorch, and Hugging Face Transformers, which offer pre-built ViT models and tools for model development. These frameworks streamline creating, training, and fine-tuning ViT models for specific tasks. ViT software provides tools for data preprocessing and augmentation, enabling the cleaning, transformation, and augmentation of image datasets to enhance model training and robustness.
On the basis of vertical, the market is divided into retail & eCommerce, media & entertainment, automotive, government, healthcare & life sciences, and others. The automotive segment recorded a remarkable revenue share in the market in 2022. ViTs identify and recognize objects on the road, including vehicles, pedestrians, cyclists, and road signs. This information is vital for making decisions and ensuring safe driving. ViTs are essential for autonomous vehicles to perceive and understand their environment. They help with object detection, path planning, obstacle avoidance, and enabling autonomous driving.
By component, the market is bifurcated into solution and professional services. In 2022, the solution segment held the highest revenue share in the market. ViT solutions make it easier for organizations to adopt ViTs by providing pre-built models, development frameworks, and libraries that streamline the development process. This accessibility encourages more businesses to explore the potential of ViTs. Solutions provide the flexibility to customize ViT models to suit specific applications and industries. This adaptability broadens the scope of ViTs and fosters their adoption in diverse sectors.
Based on application, the market is classified into image classification, image captioning, image segmentation, object detection, and others. In 2022, the object detection segment dominated the market with maximum revenue share. Object detection is essential for autonomous vehicles to identify and track objects such as pedestrians, vehicles, traffic signs, and obstacles. ViTs enhance object detection accuracy and robustness in self-driving cars. Object detection is used in surveillance systems to identify intruders, suspicious activities, and unauthorized objects. ViTs with object detection capabilities improve security and threat detection.
| Report Attribute | Details |
|---|---|
| Market size value in 2023 | USD 236.8 Million |
| Market size forecast in 2030 | USD 2.1 Billion |
| Base Year | 2023 |
| Forecast Period | 2023 to 2030 |
| Revenue Growth Rate | CAGR of 36.5% from 2023 to 2030 |
| Number of Pages | 228 |
| Number of Table | 240 |
| Report coverage | Market Trends, Revenue Estimation and Forecast, Segmentation Analysis, Regional and Country Breakdown, Porter’s 5 Forces Analysis, Company Profiling, Companies Strategic Developments, SWOT Analysis, Winning Imperatives |
| Segments covered | Component, Application, Vertical, Region |
| Country scope |
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| Companies Included | Amazon Web Services, Inc. (Amazon.com, Inc.), NVIDIA Corporation, Google LLC (Alphabet Inc.), OpenAI, L.L.C., Synopsys, Inc., Microsoft Corporation, Qualcomm Incorporated, Intel Corporation, LeewayHertz, and Clarifai, Inc. |
| Growth Drivers |
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| Restraints |
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Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. In 2022, the North America region led the market by generating the highest revenue share. North America, particularly the United States and Canada, are hubs for autonomous vehicles development. The North American healthcare sector benefits from ViTs' capabilities in interpreting complex medical images such as X-rays, CT scans, and MRIs. ViTs have transformed the retail and e-commerce landscape in North America by enabling visual search, personalized product recommendations, inventory management, and automated checkout systems, all of which enhance the shopping experience and operational efficiency.
Free Valuable Insights: Global Vision Transformers Market size to reach USD 2.1 Billion by 2030
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Amazon Web Services, Inc. (Amazon.com, Inc.), NVIDIA Corporation, Google LLC (Alphabet Inc.), OpenAI, L.L.C., Synopsys, Inc., Microsoft Corporation, Qualcomm Incorporated, Intel Corporation, LeewayHertz, and Clarifai, Inc.
By Component
By Vertical
By Application
By Geography
This Market size is expected to reach $2.1 billion by 2030.
Growing superior performance in computer vision are driving the Market in coming years, however, High installation cost of vision transformers restraints the growth of the Market.
Amazon Web Services, Inc. (Amazon.com, Inc.), NVIDIA Corporation, Google LLC (Alphabet Inc.), OpenAI, L.L.C., Synopsys, Inc., Microsoft Corporation, Qualcomm Incorporated, Intel Corporation, LeewayHertz, and Clarifai, Inc.
The expected CAGR of this Market is 36.5% from 2023 to 2030.
The Media & Entertainment segment is registering maximum revenue in the Market by Vertical in 2023;there by, achieving a market value of $736.7 Million by 2030.
The North America region is generating highest revenue in the Market by Region in 2023 and would continue to be a dominant market till 2030;there by, achieving a market value of $953.7 Million by 2030.
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