22 citations · 100 across the 15 of their papers we have counts for
4 papers · 1 filter
LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation
Jiaxin Cheng, Xiao Liang, Xingjian Shi +3
Layout-to-image generation refers to the task of synthesizing photo-realistic images based on semantic layouts. In this paper, we propose LayoutDiffuse that adapts a foundational d…
Towards Geospatial Foundation Models via Continual Pretraining
Matias Mendieta, Boran Han, Xingjian Shi +2
Geospatial technologies are becoming increasingly essential in our world for a wide range of applications, including agriculture, urban planning, and disaster response. To help imp…
Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift
Jielin Qiu, Yi Zhu, Xingjian Shi +5
Multimodal image-text models have shown remarkable performance in the past few years. However, evaluating robustness against distribution shifts is crucial before adopting them in…
Visual Prompt Tuning for Test-time Domain Adaptation
Yunhe Gao, Xingjian Shi, Yi Zhu +5
Models should be able to adapt to unseen data during test-time to avoid performance drops caused by inevitable distribution shifts in real-world deployment scenarios. In this work,…