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Home > Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 > No. 3: AAAI-22 Technical Tracks 3

TiGAN: Text-Based Interactive Image Generation and Manipulation

February 1, 2023

Authors

Yufan Zhou

University at Buffalo


Ruiyi Zhang

Adobe Research


Jiuxiang Gu

Adobe Research


Chris Tensmeyer

Adobe Research


Tong Yu

Adobe Research


Changyou Chen

University at Buffalo


Jinhui Xu

University at Buffalo


Tong Sun

Adobe Research


Proceedings:

No. 3: AAAI-22 Technical Tracks 3

Volume

Issue:

Proceedings of the AAAI Conference on Artificial Intelligence, 36

Track:

AAAI Technical Track on Computer Vision III

Downloads:

Download PDF

Abstract:

Using natural-language feedback to guide image generation and manipulation can greatly lower the required efforts and skills. This topic has received increased attention in recent years through refinement of Generative Adversarial Networks (GANs); however, most existing works are limited to single-round interaction, which is not reflective of real world interactive image editing workflows. Furthermore, previous works dealing with multi-round scenarios are limited to predefined feedback sequences, which is also impractical. In this paper, we propose a novel framework for Text-based Interactive image generation and manipulation (TiGAN) that responds to users' natural-language feedback. TiGAN utilizes the powerful pre-trained CLIP model to understand users' natural-language feedback and exploits contrastive learning for a better text-to-image mapping. To maintain the image consistency during interactions, TiGAN generates intermediate feature vectors aligned with the feedback and selectively feeds these vectors to our proposed generative model. Empirical results on several datasets show that TiGAN improves both interaction efficiency and image quality while better avoids undesirable image manipulation during interactions.

DOI:

10.1609/aaai.v36i3.20270


AAAI

Proceedings of the AAAI Conference on Artificial Intelligence, 36



Topics: AAAI

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