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Found 5 papers, 0 papers with code
An Image is Worth Multiple Words: Multi-attribute Inversion for Constrained Text-to-Image Synthesis
Another line of techniques expand the inversion space to learn multiple embeddings but they do this only along the layer dimension (e. g., one per layer of the DDPM model) or the timestep dimension (one for a set of timesteps in the denoising process), leading to suboptimal attribute disentanglement.
Iterative Multi-granular Image Editing using Diffusion Models
We hope our work would attract attention to this newly identified, pragmatic problem setting.
Learning with Difference Attention for Visually Grounded Self-supervised Representations
Recent works in self-supervised learning have shown impressive results on single-object images, but they struggle to perform well on complex multi-object images as evidenced by their poor visual grounding.
A-STAR: Test-time Attention Segregation and Retention for Text-to-image Synthesis
First, our attention segregation loss reduces the cross-attention overlap between attention maps of different concepts in the text prompt, thereby reducing the confusion/conflict among various concepts and the eventual capture of all concepts in the generated output.
MIMOQA: Multimodal Input Multimodal Output Question Answering
In this paper, we propose a novel task - MIMOQA - Multimodal Input Multimodal Output Question Answering in which the output is also multimodal.
