A Survey on Automated 2D Image to 3D Model Generation

With the rise of digital world, Traditional learning methods, while time-tested, often fall short in meeting the dynamic educational needs of today’s learners. They are constrained by several drawbacks that impede effective comprehension and engagement. This abstract sheds light on the limitations of traditional learning approaches and introduces how the integration of 3D model reconstruction can mitigate these challenges, thereby enhancing the learning experience. We proposed deep Conventional techniques, which create a virtual view from a reference picture, use two distinct steps: depth image-based rendering (DIBR) with estimated depth and depth (or disparity) estimation for the reference image and based on these steps we can create 3D model. Which allows educators to create immersive and interactive learning environments that engage students on a profound level. By converting abstract concepts into tangible and visually stimulating representations, 3D models bridge the gap between theory and practice, making complex subjects more accessible.