Erkut Erdem
@erkuterdem.bsky.social
Professor of Computer Science at Hacettepe University, Researcher in Computer Vision, Machine Learning, Artificial Intelligence, TUBA-GEBIP Outstanding Young Scientist Awardee
A huge thanks to the incredible team behind HyperGAN-CLIP! Abdul Basit Anees, Ahmet Canberk Baykal, Muhammed Burak Kizil, Duygu Ceylan @aykuterdem.bsky.social 🙌 (4/n)
November 21, 2024 at 5:52 AM
A huge thanks to the incredible team behind HyperGAN-CLIP! Abdul Basit Anees, Ahmet Canberk Baykal, Muhammed Burak Kizil, Duygu Ceylan @aykuterdem.bsky.social 🙌 (4/n)
🏮Curious to learn more? Catch us at #SIGGRAPHAsia 2024 in Tokyo or check out our paper for all the details.
Project page: cyberiada.github.io/HyperGAN-CLIP
Arxiv: arxiv.org/abs/2411.12832
(3/n)
Project page: cyberiada.github.io/HyperGAN-CLIP
Arxiv: arxiv.org/abs/2411.12832
(3/n)
November 21, 2024 at 5:52 AM
🏮Curious to learn more? Catch us at #SIGGRAPHAsia 2024 in Tokyo or check out our paper for all the details.
Project page: cyberiada.github.io/HyperGAN-CLIP
Arxiv: arxiv.org/abs/2411.12832
(3/n)
Project page: cyberiada.github.io/HyperGAN-CLIP
Arxiv: arxiv.org/abs/2411.12832
(3/n)
Our approach extends a pre-trained StyleGAN by integrating CLIP space via hypernetworks. This allows us to dynamically adapt it to new domains using reference images or text descriptions.
It’s flexible, efficient, and unlocks new applications for GANs. 🌍✨ (2/n)
It’s flexible, efficient, and unlocks new applications for GANs. 🌍✨ (2/n)
November 21, 2024 at 5:52 AM
Our approach extends a pre-trained StyleGAN by integrating CLIP space via hypernetworks. This allows us to dynamically adapt it to new domains using reference images or text descriptions.
It’s flexible, efficient, and unlocks new applications for GANs. 🌍✨ (2/n)
It’s flexible, efficient, and unlocks new applications for GANs. 🌍✨ (2/n)