no code implementations • 18 Sep 2023 • Asya Grechka, Guillaume Couairon, Matthieu Cord
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.
1 code implementation • 20 Apr 2022 • Mustafa Shukor, Guillaume Couairon, Asya Grechka, Matthieu Cord
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
1 code implementation • CVPR 2022 • Guillaume Couairon, Asya Grechka, Jakob Verbeek, Holger Schwenk, Matthieu Cord
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.