41 citations · 41 across the 9 of their papers we have counts for
6 papers · 1 filter
SceneForge: Structured World Supervision from 3D Interventions
Jizhizi Li, Jiayang Ao, Danny Wicks +1
Many multimodal learning tasks require supervision that remains consistent across edits, viewpoints, and scene-level interventions. However, such supervision is difficult to obtain…
A Practical Investigation of Spatially-Controlled Image Generation with Transformers
Guoxuan Xia, Harleen Hanspal, Petru-Daniel Tudosiu +2
Enabling image generation models to be spatially controlled is an important area of research, empowering users to better generate images according to their own fine-grained specifi…
Generating Compositional Scenes via Text-to-image RGBA Instance Generation
Alessandro Fontanella, Petru-Daniel Tudosiu, Yongxin Yang +2
Text-to-image diffusion generative models can generate high quality images at the cost of tedious prompt engineering. Controllability can be improved by introducing layout conditio…
MULAN: A Multi Layer Annotated Dataset for Controllable Text-to-Image Generation
Petru-Daniel Tudosiu, Yongxin Yang, Shifeng Zhang +5
Text-to-image generation has achieved astonishing results, yet precise spatial controllability and prompt fidelity remain highly challenging. This limitation is typically addressed…
Optimisation-Based Multi-Modal Semantic Image Editing
Bowen Li, Yongxin Yang, Steven McDonagh +3
Image editing affords increased control over the aesthetics and content of generated images. Pre-existing works focus predominantly on text-based instructions to achieve desired im…
Unsupervised 3D out-of-distribution detection with latent diffusion models
Mark S. Graham, Walter Hugo Lopez Pinaya, Paul Wright +8
Methods for out-of-distribution (OOD) detection that scale to 3D data are crucial components of any real-world clinical deep learning system. Classic denoising diffusion probabilis…