Multi-Attribute Guided Painting Generation

02/26/2020
by   Minxuan Lin, et al.
0

Controllable painting generation plays a pivotal role in image stylization. Currently, the control way of style transfer is subject to exemplar-based reference or a random one-hot vector guidance. Few works focus on decoupling the intrinsic properties of painting as control conditions, e.g., artist, genre and period. Under this circumstance, we propose a novel framework adopting multiple attributes from the painting to control the stylized results. An asymmetrical cycle structure is equipped to preserve the fidelity, associating with style preserving and attribute regression loss to keep the unique distinction of colors and textures between domains. Several qualitative and quantitative results demonstrate the effect of the combinations of multiple attributes and achieve satisfactory performance.

READ FULL TEXT

page 1

page 3

page 4

research
06/17/2023

Seen to Unseen: Exploring Compositional Generalization of Multi-Attribute Controllable Dialogue Generation

Existing controllable dialogue generation work focuses on the single-att...
research
06/02/2020

Distribution Aligned Multimodal and Multi-Domain Image Stylization

Multimodal and multi-domain stylization are two important problems in th...
research
05/04/2023

Semantic Space Grounded Weighted Decoding for Multi-Attribute Controllable Dialogue Generation

Controlling chatbot utterance generation with multiple attributes such a...
research
05/10/2023

Adapter-TST: A Parameter Efficient Method for Multiple-Attribute Text Style Transfer

Adapting a large language model for multiple-attribute text style transf...
research
09/14/2021

Controllable Dialogue Generation with Disentangled Multi-grained Style Specification and Attribute Consistency Reward

Controllable text generation is an appealing but challenging task, which...
research
02/25/2020

Unsupervised Semantic Attribute Discovery and Control in Generative Models

This work focuses on the ability to control via latent space factors sem...
research
07/01/2017

SAM: Semantic Attribute Modulation for Language Modeling and Style Variation

This paper presents a Semantic Attribute Modulation (SAM) for language m...

Please sign up or login with your details

Forgot password? Click here to reset