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Found 3 papers, 2 papers with code
Gradpaint: Gradient-Guided Inpainting with Diffusion Models
For the specific task of image inpainting, the current guiding mechanism relies on copying-and-pasting the known regions from the input image at each denoising step.
Transformer Decoders with MultiModal Regularization for Cross-Modal Food Retrieval
We propose a new retrieval framework, T-Food (Transformer Decoders with MultiModal Regularization for Cross-Modal Food Retrieval) that exploits the interaction between modalities in a novel regularization scheme, while using only unimodal encoders at test time for efficient retrieval.
Ranked #3 on
Cross-Modal Retrieval
on Recipe1M
FlexIT: Towards Flexible Semantic Image Translation
Via the latent space of an auto-encoder, we iteratively transform the input image toward the target point, ensuring coherence and quality with a variety of novel regularization terms.
