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08/21/2023
A step towards understanding why classification helps regression
A number of computer vision deep regression approaches report improved r...
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08/10/2023
Is there progress in activity progress prediction?
Activity progress prediction aims to estimate what percentage of an acti...
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08/09/2023
Objects do not disappear: Video object detection by single-frame object location anticipation
Objects in videos are typically characterized by continuous smooth motio...
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07/17/2023
Differentiable Transportation Pruning
Deep learning algorithms are increasingly employed at the edge. However,...
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05/05/2022
Evaluating Context for Deep Object Detectors
Which object detector is suitable for your context sensitive task? Deep ...
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03/16/2022
Deep vanishing point detection: Geometric priors make dataset variations vanish
Deep learning has improved vanishing point detection in images. Yet, dee...
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12/02/2021
Equal Bits: Enforcing Equally Distributed Binary Network Weights
Binary networks are extremely efficient as they use only two symbols to ...
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11/12/2021
Frequency learning for structured CNN filters with Gaussian fractional derivatives
Frequency information lies at the base of discriminating between texture...
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10/15/2021
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes
When designing Convolutional Neural Networks (CNNs), one must select the...
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08/17/2021
Investigating transformers in the decomposition of polygonal shapes as point collections
Transformers can generate predictions in two approaches: 1. auto-regress...
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08/11/2021
Zero-Shot Domain Adaptation with a Physics Prior
We explore the zero-shot setting for day-night domain adaptation. The tr...
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06/21/2021
The Arm-Swing Is Discriminative in Video Gait Recognition for Athlete Re-Identification
In this paper we evaluate running gait as an attribute for video person ...
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06/09/2021
Exploiting Learned Symmetries in Group Equivariant Convolutions
Group Equivariant Convolutions (GConvs) enable convolutional neural netw...
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06/07/2021
Resolution learning in deep convolutional networks using scale-space theory
Resolution in deep convolutional neural networks (CNNs) is typically bou...
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06/04/2021
Hallucination In Object Detection – A Study In Visual Part Verification
We show that object detectors can hallucinate and detect missing objects...
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03/29/2021
No frame left behind: Full Video Action Recognition
Not all video frames are equally informative for recognizing an action. ...
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11/26/2020
t-EVA: Time-Efficient t-SNE Video Annotation
Video understanding has received more attention in the past few years du...
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10/20/2020
Tilting at windmills: Data augmentation for deep pose estimation does not help with occlusions
Occlusion degrades the performance of human pose estimation. In this pap...
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07/18/2020
Deep Hough-Transform Line Priors
Classical work on line segment detection is knowledge-based; it uses car...
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04/16/2020
Top-Down Networks: A coarse-to-fine reimagination of CNNs
Biological vision adopts a coarse-to-fine information processing pathway...
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03/16/2020
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location
In this paper we challenge the common assumption that convolutional laye...
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09/08/2019
Cross Domain Image Matching in Presence of Outliers
Cross domain image matching between image collections from different sou...
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09/10/2018
Using phase instead of optical flow for action recognition
Currently, the most common motion representation for action recognition ...
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09/10/2018
Hand-tremor frequency estimation in videos
We focus on the problem of estimating human hand-tremor frequency from i...
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05/18/2018
Recurrent knowledge distillation
Knowledge distillation compacts deep networks by letting a small student...
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03/19/2018
Featureless: Bypassing feature extraction in action categorization
This method introduces an efficient manner of learning action categories...
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03/19/2018
Asymmetric kernel in Gaussian Processes for learning target variance
This work incorporates the multi-modality of the data distribution into ...
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03/19/2018
Deja Vu: Motion Prediction in Static Images
This paper proposes motion prediction in single still images by learning...
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03/20/2017
Active Decision Boundary Annotation with Deep Generative Models
This paper is on active learning where the goal is to reduce the data an...
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10/06/2016
Searching Scenes by Abstracting Things
In this paper we propose to represent a scene as an abstraction of 'thin...
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04/26/2016
Spot On: Action Localization from Pointly-Supervised Proposals
We strive for spatio-temporal localization of actions in videos. The sta...
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10/16/2015