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08/07/2023
On genuine invariance learning without weight-tying
In this paper, we investigate properties and limitations of invariance l...
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01/12/2023
Learning to Summarize Videos by Contrasting Clips
Video summarization aims at choosing parts of a video that narrate a sto...
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10/09/2022
LieGG: Studying Learned Lie Group Generators
Symmetries built into a neural network have appeared to be very benefici...
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05/31/2022
Contrasting quadratic assignments for set-based representation learning
The standard approach to contrastive learning is to maximize the agreeme...
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12/01/2021
Human-Object Interaction Detection via Weak Supervision
The goal of this paper is Human-object Interaction (HO-I) detection. HO-...
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11/18/2021
Wiggling Weights to Improve the Robustness of Classifiers
Robustness against unwanted perturbations is an important aspect of depl...
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10/31/2021
PIE: Pseudo-Invertible Encoder
We consider the problem of information compression from high dimensional...
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08/11/2021
Two is a crowd: tracking relations in videos
Tracking multiple objects individually differs from tracking groups of r...
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07/20/2021
Built-in Elastic Transformations for Improved Robustness
We focus on building robustness in the convolutions of neural visual cla...
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06/04/2021
DISCO: accurate Discrete Scale Convolutions
Scale is often seen as a given, disturbing factor in many vision tasks. ...
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03/21/2021
Natural Perturbed Training for General Robustness of Neural Network Classifiers
We focus on the robustness of neural networks for classification. To per...
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10/17/2020
Self-Selective Context for Interaction Recognition
Human-object interaction recognition aims for identifying the relationsh...
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10/03/2020
Adversarial and Natural Perturbations for General Robustness
In this paper we aim to explore the general robustness of neural network...
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07/17/2020
Scale Equivariance Improves Siamese Tracking
Siamese trackers turn tracking into similarity estimation between a temp...
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06/10/2020
Diagnosing Rarity in Human-Object Interaction Detection
Human-object interaction (HOI) detection is a core task in computer visi...
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01/27/2020
Explaining with Counter Visual Attributes and Examples
In this paper, we aim to explain the decisions of neural networks by uti...
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10/15/2019
Understanding Misclassifications by Attributes
In this paper, we aim to understand and explain the decisions of deep ne...
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08/06/2019
Report of 2017 NSF Workshop on Multimedia Challenges, Opportunities and Research Roadmaps
With the transformative technologies and the rapidly changing global R ...
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04/17/2019
Interpreting Adversarial Examples with Attributes
Deep computer vision systems being vulnerable to imperceptible and caref...
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03/26/2018
Long-term Tracking in the Wild: A Benchmark
We introduce a new video dataset and benchmark to assess single-object t...
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02/20/2018