429 citations · 562 across the 18 of their papers we have counts for
27 papers
Video Generation Models are General-Purpose Vision Learners
Letian Wang, Chuhan Zhang, Rishabh Kabra +9
Driven by next-token prediction, NLP shifted from task-specific models into powerful generalist foundation models. What, then, is the equivalent catalyst needed to achieve a genera…
VoCap: Video Object Captioning and Segmentation from Any Prompt
Jasper Uijlings, Xingyi Zhou, Xiuye Gu +5
Understanding objects in videos in terms of fine-grained localization masks and detailed semantic properties is a fundamental task in video understanding. In this paper, we propose…
HAMMR: HierArchical MultiModal React agents for generic VQA
Lluis Castrejon, Thomas Mensink, Howard Zhou +3
Combining Large Language Models (LLMs) with external specialized tools (LLMs+tools) is a recent paradigm to solve multimodal tasks such as Visual Question Answering (VQA). While th…
How (not) to ensemble LVLMs for VQA
Lisa Alazraki, Lluis Castrejon, Mostafa Dehghani +3
This paper studies ensembling in the era of Large Vision-Language Models (LVLMs). Ensembling is a classical method to combine different models to get increased performance. In the…
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…
The Missing Link: Finding label relations across datasets
Jasper Uijlings, Thomas Mensink, Vittorio Ferrari
Computer vision is driven by the many datasets available for training or evaluating novel methods. However, each dataset has a different set of class labels, visual definition of c…