118 citations · 258 across the 21 of their papers we have counts for
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Encyclopedic VQA: Visual questions about detailed properties of fine-grained categories
Thomas Mensink, Jasper Uijlings, Lluis Castrejon +6
We propose Encyclopedic-VQA, a large scale visual question answering (VQA) dataset featuring visual questions about detailed properties of fine-grained categories and instances. It…
Infinite Class Mixup
Thomas Mensink, Pascal Mettes
Mixup is a widely adopted strategy for training deep networks, where additional samples are augmented by interpolating inputs and labels of training pairs. Mixup has shown to impro…
Scaling Vision Transformers to 22 Billion Parameters
Mostafa Dehghani, Josip Djolonga, Basil Mustafa +39
The scaling of Transformers has driven breakthrough capabilities for language models. At present, the largest large language models (LLMs) contain upwards of 100B parameters. Visio…