Why are fewer and fewer people using cv renderer?

Due to the complexity of cv renderer, data set problems and the limitations of application scenarios, few people use cv renderer. Cv renderer is an image synthesis and rendering technology. Different from the traditional graphic renderer, cv renderer is mainly used to simulate and synthesize images in the real world, so it can be used in computer vision tasks, machine learning and other application fields. The reasons why cv renderer is used relatively infrequently are as follows:

1, complexity: cv renderer needs to simulate and synthesize real-world images, which usually involves more complex physical models and algorithms, so it requires higher hardware and computing resources.

2. Data set problem: Training cv renderer needs a lot of real images and corresponding annotation data to establish an accurate rendering model. However, it is very time-consuming to acquire and label real image data, which limits the wide application of cv renderer.

3. Limitations of application scenarios: cv renderer is mainly used in computer vision tasks and machine learning research, but it is rarely used in other fields. Therefore, compared with the traditional graphic renderer, the audience of cv renderer is relatively small.