Simon Ging

Doctoral Researcher in Computer Vision

[Simon Ging @Simon__Ging]

Thanks for sharing! It was a great experience working on this project together with you and @ThomasBrox at @CVisionFreiburg. #ICLR2024 #VLMs #AI #ComputerVision #NLP

[María A. Bravo @MariaAleBravo]

Excited to share that our paper, "Open-Ended VQA Benchmarking of Vision-Language Models by Exploiting Classification Datasets and Their Semantic Hierarchy," has been selected as a Spotlight at #ICLR2024! #AI #VLMs
Paper: https://t.co/THV7DtHOTs
Code: https://t.co/T78xHXhPP9
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[Simon Ging @Simon__Ging]

This work would not have been possible without all my amazing co-authors and supervisors: Sebastian Walter, @JelenaBratulic, Johannes Dienert, @hannahbast and Thomas Brox!

[Simon Ging @Simon__Ging]

Excited to release our models and preprint: "Using Knowledge Graphs to harvest datasets for efficient CLIP model training"

We propose a dataset collection method using knowledge graphs and web image search, and create EntityNet-33M: a dataset of 33M images paired with 46M texts.

[Simon Ging @Simon__Ging]

https://t.co/IAKpHd7I3L

[Simon Ging @Simon__Ging]

Using this dataset, we train a generic CLIP model in 2 days on 1 server.

With a 10M subset of living organisms, we train domain expert CLIP models excelling at fine-grained animal, plant, and fungi classification.

Models are out now on huggingface! The dataset is coming soon.

[Simon Ging @Simon__Ging]

Happy to present our poster: Open-ended VQA benchmarking, together with @MariaAleBravo ! #ICLR2024 @CVisionFreiburg @ThomasBrox

[María A. Bravo @MariaAleBravo]

Thanks to all collaborators at @CVisionFreiburg: @mittalsud, @ging_ai and @ThomasBrox, great job! 2/6