503 citations · 574 across the 6 of their papers we have counts for
8 papers · 1 filter
Compressed Vision for Efficient Video Understanding
Olivia Wiles, Joao Carreira, Iain Barr +2
Experience and reasoning occur across multiple temporal scales: milliseconds, seconds, hours or days. The vast majority of computer vision research, however, still focuses on indiv…
Transframer: Arbitrary Frame Prediction with Generative Models
Charlie Nash, João Carreira, Jacob Walker +4
We present a general-purpose framework for image modelling and vision tasks based on probabilistic frame prediction. Our approach unifies a broad range of tasks, from image segment…
Gradient Forward-Propagation for Large-Scale Temporal Video Modelling
Mateusz Malinowski, Dimitrios Vytiniotis, Grzegorz Swirszcz +2
How can neural networks be trained on large-volume temporal data efficiently? To compute the gradients required to update parameters, backpropagation blocks computations until the…
The Visual QA Devil in the Details: The Impact of Early Fusion and Batch Norm on CLEVR
Mateusz Malinowski, Carl Doersch
Visual QA is a pivotal challenge for higher-level reasoning, requiring understanding language, vision, and relationships between many objects in a scene. Although datasets like CLE…
Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions
M. Wagner, H. Basevi, R. Shetty +4
In-depth scene descriptions and question answering tasks have greatly increased the scope of today's definition of scene understanding. While such tasks are in principle open ended…
Learning Visual Question Answering by Bootstrapping Hard Attention
Mateusz Malinowski, Carl Doersch, Adam Santoro +1
Attention mechanisms in biological perception are thought to select subsets of perceptual information for more sophisticated processing which would be prohibitive to perform on all…