Overview: We propose a Multi-Modal Test-Time Adaptation (MM-TTA) framework that enables a model to be quickly adapted to multi-modal test data without access to the source domain training data.
Overview: We derive a new differential homography that can account for the scanline-varying camera poses in rolling shutter (RS) cameras, and demonstrate its application to carry out RS-aware image stitching and rectification at one stroke.
Overview: We make a theoretical contribution by proving that RS two-view geometry is degenerate in the case of pure translational camera motion. In view of the complex RS geometry, we then propose a convolutional neural network-based method which learns the underlying geometry (camera motion and scene structure) from just a single RS image and performs RS image correction.