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07/05/2022
SiamMask: A Framework for Fast Online Object Tracking and Segmentation
In this paper we introduce SiamMask, a framework to perform both visual ...
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03/16/2022
Attacking deep networks with surrogate-based adversarial black-box methods is easy
A recent line of work on black-box adversarial attacks has revived the u...
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01/15/2022
Parameter-free Online Test-time Adaptation
Training state-of-the-art vision models has become prohibitively expensi...
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07/05/2021
Do Different Tracking Tasks Require Different Appearance Models?
Tracking objects of interest in a video is one of the most popular and w...
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12/17/2020
On Episodes, Prototypical Networks, and Few-shot Learning
Episodic learning is a popular practice among researchers and practition...
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12/19/2019
Making Better Mistakes: Leveraging Class Hierarchies with Deep Networks
Deep neural networks have improved image classification dramatically ove...
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10/24/2019
Anchor Diffusion for Unsupervised Video Object Segmentation
Unsupervised video object segmentation has often been tackled by methods...
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06/20/2019
Let's Take This Online: Adapting Scene Coordinate Regression Network Predictions for Online RGB-D Camera Relocalisation
Many applications require a camera to be relocalised online, without exp...
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12/12/2018
Fast Online Object Tracking and Segmentation: A Unifying Approach
In this paper we illustrate how to perform both visual object tracking a...
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05/21/2018
Meta-learning with differentiable closed-form solvers
Adapting deep networks to new concepts from few examples is extremely ch...
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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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06/30/2016
Fully-Convolutional Siamese Networks for Object Tracking
The problem of arbitrary object tracking has traditionally been tackled ...
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06/16/2016
Learning feed-forward one-shot learners
One-shot learning is usually tackled by using generative models or discr...
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12/04/2015