Multi View Reconstruction

Multi-view reconstruction aims to create a complete 3D model from multiple 2D images, overcoming limitations of single-view methods. Current research focuses on improving accuracy and efficiency, particularly for sparse or noisy data, using neural implicit representations like Neural Radiance Fields (NeRFs) and incorporating techniques like diffusion models and transformers to handle complex scenes and occlusions. These advancements are significant for applications ranging from 3D modeling and virtual reality to robotics and medical imaging, offering more robust and detailed 3D representations from readily available image data.