Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: N\"UWA-LIP: Language Guided Image Inpainting with Defect-free VQGAN   Language guided image inpainting aims to fill in the defective regions of an
image under the guidance of text while keeping non-defective regions unchanged.
However, the encoding process of existing models suffers from either receptive
spreading of defective regions or information loss of non-defective regions,
giving rise to visually unappealing inpainting results. To address the above
issues, this paper proposes N\"UWA-LIP by incorporating defect-free VQGAN
(DF-VQGAN) with multi-perspective sequence to sequence (MP-S2S). In particular,
DF-VQGAN introduces relative estimation to control receptive spreading and
adopts symmetrical connections to protect information. MP-S2S further enhances
visual information from complementary perspectives, including both low-level
pixels and high-level tokens. Experiments show that DF-VQGAN performs more
robustness than VQGAN. To evaluate the inpainting performance of our model, we
built up 3 open-domain benchmarks, where N\"UWA-LIP is also superior to recent
strong baselines.

11
The categories of this paper are: hep-lat
14
The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
19
The categories of this paper are: eess
13
The categories of this paper are: quant-ph
34
The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
20
The categories of this paper are: acc-phys
30
The categories of this paper are: q-alg
22
The categories of this paper are: chao-dyn
28
The categories of this paper are: alg-geom