Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Auto-Conditioned Recurrent Networks for Extended Complex Human Motion
  Synthesis   We present a real-time method for synthesizing highly complex human motions
using a novel training regime we call the auto-conditioned Recurrent Neural
Network (acRNN). Recently, researchers have attempted to synthesize new motion
by using autoregressive techniques, but existing methods tend to freeze or
diverge after a couple of seconds due to an accumulation of errors that are fed
back into the network. Furthermore, such methods have only been shown to be
reliable for relatively simple human motions, such as walking or running. In
contrast, our approach can synthesize arbitrary motions with highly complex
styles, including dances or martial arts in addition to locomotion. The acRNN
is able to accomplish this by explicitly accommodating for autoregressive noise
accumulation during training. Our work is the first to our knowledge that
demonstrates the ability to generate over 18,000 continuous frames (300
seconds) of new complex human motion w.r.t. different styles.

4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
35
The categories of this paper are: mtrl-th
25
The categories of this paper are: patt-sol
28
The categories of this paper are: alg-geom
2
The categories of this paper are: math
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph
6
The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
15
The categories of this paper are: nucl-ex