140 citations · 375 across the 33 of their papers we have counts for
8 papers · 1 filter
Go with the Flow: Perception-refined Physics Simulation
Tom F. H. Runia, Kirill Gavrilyuk, Cees G. M. Snoek +1
For many of the physical phenomena around us, we have developed sophisticated models explaining their behavior. Nevertheless, inferring specifics from visual observations is challe…
Understanding Misclassifications by Attributes
Sadaf Gulshad, Zeynep Akata, Jan Hendrik Metzen +1
In this paper, we aim to understand and explain the decisions of deep neural networks by studying the behavior of predicted attributes when adversarial examples are introduced. We…
Scale-Equivariant Steerable Networks
Ivan Sosnovik, Michał Szmaja, Arnold Smeulders
The effectiveness of Convolutional Neural Networks (CNNs) has been substantially attributed to their built-in property of translation equivariance. However, CNNs do not have embedd…
Report of 2017 NSF Workshop on Multimedia Challenges, Opportunities and Research Roadmaps
Shih-Fu Chang, Alex Hauptmann, Louis-Philippe Morency +18
With the transformative technologies and the rapidly changing global R&D landscape, the multimedia and multimodal community is now faced with many new opportunities and uncertainti…
Model Decay in Long-Term Tracking
Efstratios Gavves, Ran Tao, Deepak K. Gupta +1
Updating the tracker model with adverse bounding box predictions adds an unavoidable bias term to the learning. This bias term, which we refer to as model decay, offsets the learni…
VideoGraph: Recognizing Minutes-Long Human Activities in Videos
Noureldien Hussein, Efstratios Gavves, Arnold W. M. Smeulders
Many human activities take minutes to unfold. To represent them, related works opt for statistical pooling, which neglects the temporal structure. Others opt for convolutional meth…
Interpreting Adversarial Examples with Attributes
Sadaf Gulshad, Jan Hendrik Metzen, Arnold Smeulders +1
Deep computer vision systems being vulnerable to imperceptible and carefully crafted noise have raised questions regarding the robustness of their decisions. We take a step back an…
Cooperative Embeddings for Instance, Attribute and Category Retrieval
William Thong, Cees G. M. Snoek, Arnold W. M. Smeulders
The goal of this paper is to retrieve an image based on instance, attribute and category similarity notions. Different from existing works, which usually address only one of these…