Large Scale Geometric Warping
Large-scale geometric warping involves transforming images or videos to align or modify their geometry, aiming for improved accuracy and efficiency in various applications. Current research focuses on developing robust and efficient warping methods, often incorporating deep learning architectures like transformers and recurrent networks, and exploring techniques such as diffeomorphic transformations and probabilistic warp consistency to handle challenges like noise, occlusion, and complex deformations. These advancements are significantly impacting fields like computer vision (e.g., virtual try-on, stereo matching, face animation), and signal processing (e.g., time series analysis), enabling more accurate and realistic image manipulation and analysis.