Many video enhancement algorithms rely on optical flow to register frames in a video
sequence. Precise flow estimation is however intractable; and optical flow itself is often a …

Feature warping is a core technique in optical flow estimation; however, the ambiguity
caused by occluded areas during warping is a major problem that remains unsolved. In this …

Convolutional neural networks (CNNs) have recently been very successful in a variety of
computer vision tasks, especially on those linked to recognition. Optical flow estimation has …

Convolutional neural networks (CNNs) have recently been very successful in a variety of
computer vision tasks, especially on those linked to recognition. Optical flow estimation has …

Optical flow estimation is one of the oldest and still most active research domains in
computer vision. In 35 years, many methodological concepts have been introduced and …

The accuracy of optical flow estimation algorithms has been improving steadily as
evidenced by results on the Middlebury optical flow benchmark. The typical formulation …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

The accuracy of optical flow estimation algorithms has been improving steadily as
evidenced by results on the Middlebury optical flow benchmark. The typical formulation …

The quantitative evaluation of optical flow algorithms by Barron et al.(1994) led to significant
advances in performance. The challenges for optical flow algorithms today go beyond the …

Modern large displacement optical flow algorithms usually use an initialization by either
sparse descriptor matching techniques or dense approximate nearest neighbor fields. While …