Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: GraftNet: Towards Domain Generalized Stereo Matching with a
  Broad-Spectrum and Task-Oriented Feature   Although supervised deep stereo matching networks have made impressive
achievements, the poor generalization ability caused by the domain gap prevents
them from being applied to real-life scenarios. In this paper, we propose to
leverage the feature of a model trained on large-scale datasets to deal with
the domain shift since it has seen various styles of images. With the cosine
similarity based cost volume as a bridge, the feature will be grafted to an
ordinary cost aggregation module. Despite the broad-spectrum representation,
such a low-level feature contains much general information which is not aimed
at stereo matching. To recover more task-specific information, the grafted
feature is further input into a shallow network to be transformed before
calculating the cost. Extensive experiments show that the model generalization
ability can be improved significantly with this broad-spectrum and
task-oriented feature. Specifically, based on two well-known architectures
PSMNet and GANet, our methods are superior to other robust algorithms when
transferring from SceneFlow to KITTI 2015, KITTI 2012, and Middlebury. Code is
available at https://github.com/SpadeLiu/Graft-PSMNet.

17
The categories of this paper are: q-fin
33
The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc
19
The categories of this paper are: eess
4
The categories of this paper are: cond-mat
9
The categories of this paper are: nlin
25
The categories of this paper are: patt-sol
16
The categories of this paper are: stat
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
12
The categories of this paper are: nucl-th
22
The categories of this paper are: chao-dyn
7
The categories of this paper are: hep-th
21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
13
The categories of this paper are: quant-ph