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Name: CompVis - Computer Vision and Learning LMU Munich

Type: Organization

Bio: Computer Vision and Learning research group at Ludwig Maximilian University of Munich (formerly Computer Vision Group at Heidelberg University)

Location: Germany

Blog: https://ommer-lab.com/

CompVis - Computer Vision and Learning LMU Munich's Projects

cliquecnn icon cliquecnn

Code for our paper "CliqueCNN: Deep Unsupervised Exemplar Learning" https://arxiv.org/abs/1608.08792

cuneiform-sign-detection-dataset icon cuneiform-sign-detection-dataset

Dataset provided with the article "Deep learning for cuneiform sign detection with weak supervision using transliteration alignment". It comprises image references, transliterations and sign annotations of clay tablets from the Neo-Assyrian epoch.

cuneiform-sign-detection-webapp icon cuneiform-sign-detection-webapp

Code for demo web application of the article "Deep learning for cuneiform sign detection with weak supervision using transliteration alignment".

depth-fm icon depth-fm

DepthFM: Fast Monocular Depth Estimation with Flow Matching

fm-boosting icon fm-boosting

FMBoost: Boosting Latent Diffusion with Flow Matching (ECCV 2024 Oral)

hbugen2018 icon hbugen2018

Towards Learning a Realistic Rendering of Human Behavior

iin icon iin

A Disentangling Invertible Interpretation Network

imagebart icon imagebart

ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis

invariances icon invariances

Making Sense of CNNs: Interpreting Deep Representations & Their Invariances with Invertible Neural Networks

ipoke icon ipoke

iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis

net2net icon net2net

Network-to-Network Translation with Conditional Invertible Neural Networks

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