With the emergence of Artificial Intelligence (AI), there are many applications for 3D computer vision, and different problems in diversified domains are being solved. Particularly deep learning and image processing techniques are widely used in computer vision applications, for example, medical imaging which commonly uses 2D images to see human organs can benefit tremendously from 3D reconstruction of a human organ or cancer lesions for diagnosis purposes. Cars nowadays use radar, lidar, and sensors to create an awareness of the surroundings of the car, having a 3D reconstruction of the car’s surroundings will provide a better situational awareness. In many computer vision applications, it is essential to use image conversion techniques. With AI in place, learning-based approaches became popular along with image processing techniques. Towards this end, this paper throws light on those methods with a systematic literature review. The insights presented in this paper can help in further research in computer vision applications.
Mamand et al. (Fri,) studied this question.