1 code implementation • 15 Dec 2023 • Noël Vouitsis, Zhaoyan Liu, Satya Krishna Gorti, Valentin Villecroze, Jesse C. Cresswell, Guangwei Yu, Gabriel Loaiza-Ganem, Maksims Volkovs
The goal of multimodal alignment is to learn a single latent space that is shared between multimodal inputs.
2 code implementations • NeurIPS 2023 • George Stein, Jesse C. Cresswell, Rasa Hosseinzadeh, Yi Sui, Brendan Leigh Ross, Valentin Villecroze, Zhaoyan Liu, Anthony L. Caterini, J. Eric T. Taylor, Gabriel Loaiza-Ganem
Comparing to 17 modern metrics for evaluating the overall performance, fidelity, diversity, rarity, and memorization of generative models, we find that the state-of-the-art perceptual realism of diffusion models as judged by humans is not reflected in commonly reported metrics such as FID.
2 code implementations • 26 Apr 2023 • Zhaoyan Liu, Noel Vouitsis, Satya Krishna Gorti, Jimmy Ba, Gabriel Loaiza-Ganem
We propose TR0N, a highly general framework to turn pre-trained unconditional generative models, such as GANs and VAEs, into conditional models.
Ranked #31 on Text-to-Image Generation on MS COCO
no code implementations • 17 May 2021 • Andrey Ignatov, Grigory Malivenko, Radu Timofte, Sheng Chen, Xin Xia, Zhaoyan Liu, Yuwei Zhang, Feng Zhu, Jiashi Li, Xuefeng Xiao, Yuan Tian, Xinglong Wu, Christos Kyrkou, Yixin Chen, Zexin Zhang, Yunbo Peng, Yue Lin, Saikat Dutta, Sourya Dipta Das, Nisarg A. Shah, Himanshu Kumar, Chao Ge, Pei-Lin Wu, Jin-Hua Du, Andrew Batutin, Juan Pablo Federico, Konrad Lyda, Levon Khojoyan, Abhishek Thanki, Sayak Paul, Shahid Siddiqui
To address this problem, we introduce the first Mobile AI challenge, where the target is to develop quantized deep learning-based camera scene classification solutions that can demonstrate a real-time performance on smartphones and IoT platforms.