1 code implementation • 21 Feb 2024 • Hikaru Shindo, Manuel Brack, Gopika Sudhakaran, Devendra Singh Dhami, Patrick Schramowski, Kristian Kersting
To remedy this issue, we propose DeiSAM -- a combination of large pre-trained neural networks with differentiable logic reasoners -- for deictic promptable segmentation.
no code implementations • 28 Nov 2023 • Manuel Brack, Felix Friedrich, Katharina Kornmeier, Linoy Tsaban, Patrick Schramowski, Kristian Kersting, Apolinário Passos
Second, our methodology supports multiple simultaneous edits and is architecture-agnostic.
no code implementations • 20 Sep 2023 • Manuel Brack, Patrick Schramowski, Kristian Kersting
Text-conditioned image generation models have recently achieved astonishing image quality and alignment results.
1 code implementation • 15 Sep 2023 • Wolfgang Stammer, Felix Friedrich, David Steinmann, Manuel Brack, Hikaru Shindo, Kristian Kersting
Current AI research mainly treats explanations as a means for model inspection.
no code implementations • 28 May 2023 • Manuel Brack, Felix Friedrich, Patrick Schramowski, Kristian Kersting
Text-conditioned image generation models have recently achieved astonishing results in image quality and text alignment and are consequently employed in a fast-growing number of applications.
1 code implementation • NeurIPS 2023 • Marco Bellagente, Manuel Brack, Hannah Teufel, Felix Friedrich, Björn Deiseroth, Constantin Eichenberg, Andrew Dai, Robert Baldock, Souradeep Nanda, Koen Oostermeijer, Andres Felipe Cruz-Salinas, Patrick Schramowski, Kristian Kersting, Samuel Weinbach
The recent popularity of text-to-image diffusion models (DM) can largely be attributed to the intuitive interface they provide to users.
1 code implementation • 16 Mar 2023 • Lukas Struppek, Dominik Hintersdorf, Felix Friedrich, Manuel Brack, Patrick Schramowski, Kristian Kersting
Neural network-based image classifiers are powerful tools for computer vision tasks, but they inadvertently reveal sensitive attribute information about their classes, raising concerns about their privacy.
1 code implementation • 7 Feb 2023 • Felix Friedrich, Manuel Brack, Lukas Struppek, Dominik Hintersdorf, Patrick Schramowski, Sasha Luccioni, Kristian Kersting
Generative AI models have recently achieved astonishing results in quality and are consequently employed in a fast-growing number of applications.
1 code implementation • NeurIPS 2023 • Manuel Brack, Felix Friedrich, Dominik Hintersdorf, Lukas Struppek, Patrick Schramowski, Kristian Kersting
This leaves the user with little semantic control.
1 code implementation • NeurIPS 2023 • Björn Deiseroth, Mayukh Deb, Samuel Weinbach, Manuel Brack, Patrick Schramowski, Kristian Kersting
Generative transformer models have become increasingly complex, with large numbers of parameters and the ability to process multiple input modalities.
2 code implementations • 12 Dec 2022 • Manuel Brack, Patrick Schramowski, Felix Friedrich, Dominik Hintersdorf, Kristian Kersting
Large, text-conditioned generative diffusion models have recently gained a lot of attention for their impressive performance in generating high-fidelity images from text alone.
2 code implementations • CVPR 2023 • Patrick Schramowski, Manuel Brack, Björn Deiseroth, Kristian Kersting
Text-conditioned image generation models have recently achieved astonishing results in image quality and text alignment and are consequently employed in a fast-growing number of applications.
2 code implementations • 19 Sep 2022 • Lukas Struppek, Dominik Hintersdorf, Felix Friedrich, Manuel Brack, Patrick Schramowski, Kristian Kersting
Models for text-to-image synthesis, such as DALL-E~2 and Stable Diffusion, have recently drawn a lot of interest from academia and the general public.
3 code implementations • 15 Sep 2022 • Dominik Hintersdorf, Lukas Struppek, Manuel Brack, Felix Friedrich, Patrick Schramowski, Kristian Kersting
Our large-scale experiments on CLIP demonstrate that individuals used for training can be identified with very high accuracy.
1 code implementation • 17 Aug 2022 • Manuel Brack, Patrick Schramowski, Björn Deiseroth, Kristian Kersting
Bootstrapping from pre-trained language models has been proven to be an efficient approach for building vision-language models (VLM) for tasks such as image captioning or visual question answering.