Deep ordinal regression network for monocular depth estimation
Monocular depth estimation, which plays a crucial role in understanding 3D scene
geometry, is an ill-posed prob-lem. Recent methods have gained significant improvement by …
geometry, is an ill-posed prob-lem. Recent methods have gained significant improvement by …
Monocular depth estimation using laplacian pyramid-based depth residuals
With a great success of the generative model via deep neural networks, monocular depth
estimation has been actively studied by exploiting various encoder-decoder architectures …
estimation has been actively studied by exploiting various encoder-decoder architectures …
DPNet: Detail-preserving network for high quality monocular depth estimation
Existing monocular depth estimation methods are unsatisfactory due to the inaccurate
inference of depth details and the loss of spatial information. In this paper, we present a …
inference of depth details and the loss of spatial information. In this paper, we present a …
Modeling defocus-disparity in dual-pixel sensors
Most modern consumer cameras use dual-pixel (DP) sensors that provide two sub-aperture
views of the scene in a single photo capture. The DP sensor was designed to assist the …
views of the scene in a single photo capture. The DP sensor was designed to assist the …