37 citations · 55 across the 8 of their papers we have counts for
8 papers · 1 filter
ViCo: Engaging Video Comment Generation with Human Preference Rewards
Yuchong Sun, Bei Liu, Xu Chen +2
Engaging video comments play an important role in video social media, as they are the carrier of feelings, thoughts, or humor of the audience. Preliminary works have made initial e…
Improving Diversity in Zero-Shot GAN Adaptation with Semantic Variations
Seogkyu Jeon, Bei Liu, Pilhyeon Lee +3
Training deep generative models usually requires a large amount of data. To alleviate the data collection cost, the task of zero-shot GAN adaptation aims to reuse well-trained gene…
Revisiting Latent Space of GAN Inversion for Real Image Editing
Kai Katsumata, Duc Minh Vo, Bei Liu +1
The exploration of the latent space in StyleGANs and GAN inversion exemplify impressive real-world image editing, yet the trade-off between reconstruction quality and editing quali…
Balancing Reconstruction and Editing Quality of GAN Inversion for Real Image Editing with StyleGAN Prior Latent Space
Kai Katsumata, Duc Minh Vo, Bei Liu +1
The exploration of the latent space in StyleGANs and GAN inversion exemplify impressive real-world image editing, yet the trade-off between reconstruction quality and editing quali…
AI Illustrator: Translating Raw Descriptions into Images by Prompt-based Cross-Modal Generation
Yiyang Ma, Huan Yang, Bei Liu +2
AI illustrator aims to automatically design visually appealing images for books to provoke rich thoughts and emotions. To achieve this goal, we propose a framework for translating…
A Picture is Worth a Thousand Words: A Unified System for Diverse Captions and Rich Images Generation
Yupan Huang, Bei Liu, Jianlong Fu +1
A creative image-and-text generative AI system mimics humans' extraordinary abilities to provide users with diverse and comprehensive caption suggestions, as well as rich image cre…