Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dimensions of Motion: Learning to Predict a Subspace of Optical Flow
  from a Single Image   We introduce the problem of predicting, from a single video frame, a
low-dimensional subspace of optical flow which includes the actual
instantaneous optical flow. We show how several natural scene assumptions allow
us to identify an appropriate flow subspace via a set of basis flow fields
parameterized by disparity and a representation of object instances. The flow
subspace, together with a novel loss function, can be used for the tasks of
predicting monocular depth or predicting depth plus an object instance
embedding. This provides a new approach to learning these tasks in an
unsupervised fashion using monocular input video without requiring camera
intrinsics or poses.

12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
0
The categories of this paper are: hep-ph
8
The categories of this paper are: hep-ex
36
The categories of this paper are: cmp-lg
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
15
The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat
17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
19
The categories of this paper are: eess