Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The GIST and RIST of Iterative Self-Training for Semi-Supervised
  Segmentation   We consider the task of semi-supervised semantic segmentation, where we aim
to produce pixel-wise semantic object masks given only a small number of
human-labeled training examples. We focus on iterative self-training methods in
which we explore the behavior of self-training over multiple refinement stages.
We show that iterative self-training leads to performance degradation if done
na\"ively with a fixed ratio of human-labeled to pseudo-labeled training
examples. We propose Greedy Iterative Self-Training (GIST) and Random Iterative
Self-Training (RIST) strategies that alternate between training on either
human-labeled data or pseudo-labeled data at each refinement stage, resulting
in a performance boost rather than degradation. We further show that GIST and
RIST can be combined with existing semi-supervised learning methods to boost
performance.

31
The categories of this paper are: ao-sci
16
The categories of this paper are: stat
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph
24
The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
35
The categories of this paper are: mtrl-th
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
12
The categories of this paper are: nucl-th
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an