ViT-SGAN modifies ViTGAN's self-attention with mean-variance and texton descriptors to synthesize textures, but the evaluation is too weak and the equations are too unclear to support the claimed gains.
Textons, the elements of texture perception, and their interactions,,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
method 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
REJECT 1roles
method 1polarities
use method 1representative citing papers
citing papers explorer
-
Texture Image Synthesis Using Spatial GAN Based on Vision Transformers
ViT-SGAN modifies ViTGAN's self-attention with mean-variance and texton descriptors to synthesize textures, but the evaluation is too weak and the equations are too unclear to support the claimed gains.