Upsampling Operation

Upsampling, the process of increasing the resolution of data, is a crucial operation across diverse fields like image processing, point cloud generation, and signal processing. Current research focuses on improving upsampling techniques' efficiency and fidelity, exploring various architectures including transformers, convolutional neural networks, and implicit neural representations, often within a coarse-to-fine or iterative refinement framework. These advancements are driving improvements in applications ranging from medical image segmentation and robotic perception to super-resolution imaging and efficient 3D model generation, impacting both the accuracy and computational cost of these tasks. The development of more robust and efficient upsampling methods remains a significant area of ongoing investigation.