Nick Stracke
I'm a PhD student in the CompVis group advised by Björn Ommer (LMU). My research focuses on efficient methods to control and alter diffusion T2I models. This includes extending them to perform efficient video generation as well finding disentangled representations for more fine-grained control.
News 🔥
- July 2024 One first author paper and one co-author paper accpeted to ECCV2024.
- November 2023 Joined the CompVis Group at LMU spearheaded by Björn Ommer.
Research
CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models
Nick Stracke, Stefan A Baumann, Joshua M Susskind, Miguel A Bautista, Björn Ommer
ECCV 2024
Project Page / arXiv / CodeLoRAs don't have to be static! They can also introduce new conditioning into foundation models more efficiently and effectively than previous methods.
Continuous, Subject-Specific Attribute Control in T2I Models by Identifying Semantic Directions
Stefan Andreas Baumann, Felix Krause, Michael Neumayr, Nick Stracke, Vincent Tao Hu, Björn Ommer
Preprint 2024
Project Page / arXiv / Code / Colab / TwitterT2I diffusion models alredy knew how to do fine-grained control, we just had to learn out how to leverage this capability.
Boosting Latent Diffusion with Flow Matching
Johannes Fischer*, Ming Gui*, Pingchuan Ma*, Nick Stracke, Stefan Andreas Baumann, Björn Ommer
ECCV 2024 (Oral)
Project Page / arXiv / CodeMaking high-resolution T2I diffusion fast and increasing resolutions to multiple megapixels by adding flow matching-based superresolution stages in latent space.