Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: MS-TCN++: Multi-Stage Temporal Convolutional Network for Action
  Segmentation   With the success of deep learning in classifying short trimmed videos, more
attention has been focused on temporally segmenting and classifying activities
in long untrimmed videos. State-of-the-art approaches for action segmentation
utilize several layers of temporal convolution and temporal pooling. Despite
the capabilities of these approaches in capturing temporal dependencies, their
predictions suffer from over-segmentation errors. In this paper, we propose a
multi-stage architecture for the temporal action segmentation task that
overcomes the limitations of the previous approaches. The first stage generates
an initial prediction that is refined by the next ones. In each stage we stack
several layers of dilated temporal convolutions covering a large receptive
field with few parameters. While this architecture already performs well, lower
layers still suffer from a small receptive field. To address this limitation,
we propose a dual dilated layer that combines both large and small receptive
fields. We further decouple the design of the first stage from the refining
stages to address the different requirements of these stages. Extensive
evaluation shows the effectiveness of the proposed model in capturing
long-range dependencies and recognizing action segments. Our models achieve
state-of-the-art results on three datasets: 50Salads, Georgia Tech Egocentric
Activities (GTEA), and the Breakfast dataset.

18
The categories of this paper are: econ
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat
3
The categories of this paper are: physics
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph
29
The categories of this paper are: funct-an
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph
27
The categories of this paper are: comp-gas
10
The categories of this paper are: q-bio