Search Results for author: Aishwarya Agarwal

Found 5 papers, 0 papers with code

An Image is Worth Multiple Words: Multi-attribute Inversion for Constrained Text-to-Image Synthesis

no code implementations20 Nov 2023 Aishwarya Agarwal, Srikrishna Karanam, Tripti Shukla, Balaji Vasan Srinivasan

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.

Denoising Disentanglement +1

Learning with Difference Attention for Visually Grounded Self-supervised Representations

no code implementations26 Jun 2023 Aishwarya Agarwal, Srikrishna Karanam, Balaji Vasan Srinivasan

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.

Self-Supervised Learning Visual Grounding

A-STAR: Test-time Attention Segregation and Retention for Text-to-image Synthesis

no code implementations ICCV 2023 Aishwarya Agarwal, Srikrishna Karanam, K J Joseph, Apoorv Saxena, Koustava Goswami, Balaji Vasan Srinivasan

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.

Denoising Image Generation +1

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