Reconstruction Transformer

Reconstruction Transformers are a class of neural network models leveraging transformer architectures to perform various reconstruction tasks, primarily focusing on high-quality image and 3D model generation from incomplete or noisy data. Current research emphasizes improving model robustness, particularly by addressing aliasing issues and incorporating geometric awareness for more accurate 3D reconstruction. These advancements are driven by the need for efficient and accurate reconstruction in applications ranging from image restoration to 3D modeling, impacting fields like computer vision and graphics.