activity
20142022
most citedA Multi-World Approach to Question Answering about Real-World Scenes based on Uncertain Input

257 citations · 293 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2022

Neural Payoff Machines: Predicting Fair and Stable Payoff Allocations Among Team Members

Daphne Cornelisse, Thomas Rood, Mateusz Malinowski +2

In many multi-agent settings, participants can form teams to achieve collective outcomes that may far surpass their individual capabilities. Measuring the relative contributions of…

cs.CV20162 cited

Tutorial on Answering Questions about Images with Deep Learning

Mateusz Malinowski, Mario Fritz

Together with the development of more accurate methods in Computer Vision and Natural Language Understanding, holistic architectures that answer on questions about the content of r…

cs.CV20164 cited

Mean Box Pooling: A Rich Image Representation and Output Embedding for the Visual Madlibs Task

Ashkan Mokarian, Mateusz Malinowski, Mario Fritz

We present Mean Box Pooling, a novel visual representation that pools over CNN representations of a large number, highly overlapping object proposals. We show that such representat…

cs.AI20155 cited

Hard to Cheat: A Turing Test based on Answering Questions about Images

Mateusz Malinowski, Mario Fritz

Progress in language and image understanding by machines has sparkled the interest of the research community in more open-ended, holistic tasks, and refueled an old AI dream of bui…

cs.CV201425 cited

A Pooling Approach to Modelling Spatial Relations for Image Retrieval and Annotation

Mateusz Malinowski, Mario Fritz

Over the last two decades we have witnessed strong progress on modeling visual object classes, scenes and attributes that have significantly contributed to automated image understa…

cs.AI2014257 cited

A Multi-World Approach to Question Answering about Real-World Scenes based on Uncertain Input

Mateusz Malinowski, Mario Fritz

We propose a method for automatically answering questions about images by bringing together recent advances from natural language processing and computer vision. We combine discret…