Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Pseudo-labelling and Meta Reweighting Learning for Image Aesthetic
  Quality Assessment   In the tasks of image aesthetic quality evaluation, it is difficult to reach
both the high score area and low score area due to the normal distribution of
aesthetic datasets. To reduce the error in labeling and solve the problem of
normal data distribution, we propose a new aesthetic mixed dataset with
classification and regression called AMD-CR, and we train a meta reweighting
network to reweight the loss of training data differently. In addition, we
provide a training strategy acccording to different stages, based on pseudo
labels of the binary classification task, and then we use it for aesthetic
training acccording to different stages in classification and regression tasks.
In the construction of the network structure, we construct an aesthetic
adaptive block (AAB) structure that can adapt to any size of the input images.
Besides, we also use the efficient channel attention (ECA) to strengthen the
feature extracting ability of each task. The experimental result shows that our
method improves 0.1112 compared with the conventional methods in SROCC. The
method can also help to find best aesthetic path planning for unmanned aerial
vehicles (UAV) and vehicles.

13
The categories of this paper are: quant-ph
11
The categories of this paper are: hep-lat
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
19
The categories of this paper are: eess
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
12
The categories of this paper are: nucl-th
6
The categories of this paper are: astro-ph
9
The categories of this paper are: nlin
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph