Warping Method

Image warping methods aim to transform images or 3D models by deforming their geometry or appearance, achieving tasks like surface reconstruction, depth estimation, and style transfer. Current research focuses on improving accuracy and efficiency through techniques like progressive view planning, cycle-consistent constraints, and neural implicit representations, often incorporating deep learning architectures such as convolutional neural networks and transformers. These advancements are impacting diverse fields, enabling improvements in computer vision, graphics, and robotics applications such as 3D modeling, video processing, and augmented reality.