Deep 3D World Models for Multi-Image Super-Resolution Beyond Optical
  Flow
Luca Savant Aira Diego Valsesia Andrea Bordone Molini Giulia Fracastoro Enrico Magli Andrea Mirabile
Multi-image super-resolution (MISR) allows to increase the spatial resolution
of a low-resolution (LR) acquisition by combining multiple images carrying
complementary information in the form of sub-pixel offsets in the scene
sampling, and can be significantly more effective than its single-image
counterpart. Its main difficulty lies in accurately registering and fusing the
multi-image information. Currently studied settings, such as burst photography,
typically involve assumptions of small geometric disparity between the LR
images and rely on optical flow for image registration. We study a MISR method
that can increase the resolution of sets of images acquired with arbitrary, and
potentially wildly different, camera positions and orientations, generalizing
the currently studied MISR settings. Our proposed model, called EpiMISR, moves
away from optical flow and explicitly uses the epipolar geometry of the
acquisition process, together with transformer-based processing of radiance
feature fields to substantially improve over state-of-the-art MISR methods in
presence of large disparities in the LR images.