Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Unsupervised Video Understanding by Reconciliation of Posture
  Similarities   Understanding human activity and being able to explain it in detail surpasses
mere action classification by far in both complexity and value. The challenge
is thus to describe an activity on the basis of its most fundamental
constituents, the individual postures and their distinctive transitions.
Supervised learning of such a fine-grained representation based on elementary
poses is very tedious and does not scale. Therefore, we propose a completely
unsupervised deep learning procedure based solely on video sequences, which
starts from scratch without requiring pre-trained networks, predefined body
models, or keypoints. A combinatorial sequence matching algorithm proposes
relations between frames from subsets of the training data, while a CNN is
reconciling the transitivity conflicts of the different subsets to learn a
single concerted pose embedding despite changes in appearance across sequences.
Without any manual annotation, the model learns a structured representation of
postures and their temporal development. The model not only enables retrieval
of similar postures but also temporal super-resolution. Additionally, based on
a recurrent formulation, next frames can be synthesized.

22
The categories of this paper are: chao-dyn
35
The categories of this paper are: mtrl-th
9
The categories of this paper are: nlin
3
The categories of this paper are: physics
36
The categories of this paper are: cmp-lg
7
The categories of this paper are: hep-th
8
The categories of this paper are: hep-ex
2
The categories of this paper are: math
11
The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
14
The categories of this paper are: math-ph
29
The categories of this paper are: funct-an
16
The categories of this paper are: stat
10
The categories of this paper are: q-bio