Exploring 3D Representations in Computer Vision

This chapter discusses the contrast between 2D and 2.5D images in enhancing computer vision, emphasizing the importance of depth information for geometry reconstruction. It delves into the complexities of neural scene representations, exploring dynamic deformability, the advantages of continuous models over discrete ones, and the challenges in meta-learning optimization. By reflecting on influential research and the significance of 3D structure, the chapter highlights innovative perspectives and the future direction of computer vision technology.