Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Structure-Attentioned Memory Network for Monocular Depth Estimation   Monocular depth estimation is a challenging task that aims to predict a
corresponding depth map from a given single RGB image. Recent deep learning
models have been proposed to predict the depth from the image by learning the
alignment of deep features between the RGB image and the depth domains. In this
paper, we present a novel approach, named Structure-Attentioned Memory Network,
to more effectively transfer domain features for monocular depth estimation by
taking into account the common structure regularities (e.g., repetitive
structure patterns, planar surfaces, symmetries) in domain adaptation. To this
end, we introduce a new Structure-Oriented Memory (SOM) module to learn and
memorize the structure-specific information between RGB image domain and the
depth domain. More specifically, in the SOM module, we develop a Memorable Bank
of Filters (MBF) unit to learn a set of filters that memorize the
structure-aware image-depth residual pattern, and also an Attention Guided
Controller (AGC) unit to control the filter selection in the MBF given image
features queries. Given the query image feature, the trained SOM module is able
to adaptively select the best customized filters for cross-domain feature
transferring with an optimal structural disparity between image and depth. In
summary, we focus on addressing this structure-specific domain adaption
challenge by proposing a novel end-to-end multi-scale memorable network for
monocular depth estimation. The experiments show that our proposed model
demonstrates the superior performance compared to the existing supervised
monocular depth estimation approaches on the challenging KITTI and NYU Depth V2
benchmarks.

20
The categories of this paper are: acc-phys
23
The categories of this paper are: solv-int
10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex
28
The categories of this paper are: alg-geom
4
The categories of this paper are: cond-mat
32
The categories of this paper are: atom-ph
12
The categories of this paper are: nucl-th
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
35
The categories of this paper are: mtrl-th
17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org