Search Results for author: Pascal Mettes

Found 30 papers, 17 papers with code

Maximum Class Separation as Inductive Bias in One Matrix

1 code implementation17 Jun 2022 Tejaswi Kasarla, Gertjan J. Burghouts, Max van Spengler, Elise van der Pol, Rita Cucchiara, Pascal Mettes

This paper proposes a simple alternative: encoding maximum separation as an inductive bias in the network by adding one fixed matrix multiplication before computing the softmax activations.

Inductive Bias Long-tail Learning +3

Less than Few: Self-Shot Video Instance Segmentation

no code implementations19 Apr 2022 Pengwan Yang, Yuki M. Asano, Pascal Mettes, Cees G. M. Snoek

The goal of this paper is to bypass the need for labelled examples in few-shot video understanding at run time.

Few-Shot Learning Instance Segmentation +4

Hyperbolic Image Segmentation

1 code implementation CVPR 2022 Mina GhadimiAtigh, Julian Schoep, Erman Acar, Nanne van Noord, Pascal Mettes

For image segmentation, the current standard is to perform pixel-level optimization and inference in Euclidean output embedding spaces through linear hyperplanes.

Semantic Segmentation

Universal Prototype Transport for Zero-Shot Action Recognition and Localization

no code implementations8 Mar 2022 Pascal Mettes

For universal action models, we first seek to find a hyperspherical optimal transport mapping from unseen action prototypes to the set of all projected test videos.

Action Recognition Temporal Localization +2

Zero-Shot Action Recognition from Diverse Object-Scene Compositions

1 code implementation26 Oct 2021 Carlo Bretti, Pascal Mettes

This paper investigates the problem of zero-shot action recognition, in the setting where no training videos with seen actions are available.

Action Recognition Transfer Learning +1

Diagnosing Errors in Video Relation Detectors

1 code implementation25 Oct 2021 Shuo Chen, Pascal Mettes, Cees G. M. Snoek

Video relation detection forms a new and challenging problem in computer vision, where subjects and objects need to be localized spatio-temporally and a predicate label needs to be assigned if and only if there is an interaction between the two.

Action Localization object-detection +1

Transductive Universal Transport for Zero-Shot Action Recognition

no code implementations29 Sep 2021 Pascal Mettes

For universal object models, we outline a weighted transport variant from unseen action embeddings to object embeddings directly.

Action Recognition Temporal Localization +2

Social Fabric: Tubelet Compositions for Video Relation Detection

1 code implementation ICCV 2021 Shuo Chen, Zenglin Shi, Pascal Mettes, Cees G. M. Snoek

We also propose Social Fabric: an encoding that represents a pair of object tubelets as a composition of interaction primitives.

Frequency-Supervised MR-to-CT Image Synthesis

1 code implementation19 Jul 2021 Zenglin Shi, Pascal Mettes, Guoyan Zheng, Cees Snoek

In this paper, we find that all existing approaches share a common limitation: reconstruction breaks down in and around the high-frequency parts of CT images.

Computed Tomography (CT) Image Generation +1

On Measuring and Controlling the Spectral Bias of the Deep Image Prior

1 code implementation2 Jul 2021 Zenglin Shi, Pascal Mettes, Subhransu Maji, Cees G. M. Snoek

The deep image prior showed that a randomly initialized network with a suitable architecture can be trained to solve inverse imaging problems by simply optimizing it's parameters to reconstruct a single degraded image.

Denoising Super-Resolution

Unsharp Mask Guided Filtering

1 code implementation2 Jun 2021 Zenglin Shi, Yunlu Chen, Efstratios Gavves, Pascal Mettes, Cees G. M. Snoek

The state-of-the-art leverages deep networks to estimate the two core coefficients of the guided filter.

Denoising

Object Priors for Classifying and Localizing Unseen Actions

1 code implementation10 Apr 2021 Pascal Mettes, William Thong, Cees G. M. Snoek

This work strives for the classification and localization of human actions in videos, without the need for any labeled video training examples.

Action Classification Action Localization +2

Localizing the Common Action Among a Few Videos

1 code implementation ECCV 2020 Pengwan Yang, Vincent Tao Hu, Pascal Mettes, Cees G. M. Snoek

The start and end of an action in a long untrimmed video is determined based on just a hand-full of trimmed video examples containing the same action, without knowing their common class label.

Action Localization

Open Cross-Domain Visual Search

2 code implementations19 Nov 2019 William Thong, Pascal Mettes, Cees G. M. Snoek

In this paper, we make the step towards an open setting where multiple visual domains are available.

Domain Adaptation

4-Connected Shift Residual Networks

1 code implementation22 Oct 2019 Andrew Brown, Pascal Mettes, Marcel Worring

Interestingly, when incorporating shifts to all point-wise convolutions in residual networks, 4-connected shifts outperform 8-connected shifts.

Counting with Focus for Free

1 code implementation ICCV 2019 Zenglin Shi, Pascal Mettes, Cees G. M. Snoek

To assist both the density estimation and the focus from segmentation, we also introduce an improved kernel size estimator for the point annotations.

Density Estimation

Hyperspherical Prototype Networks

1 code implementation NeurIPS 2019 Pascal Mettes, Elise van der Pol, Cees G. M. Snoek

This paper introduces hyperspherical prototype networks, which unify classification and regression with prototypes on hyperspherical output spaces.

Classification General Classification

Spatio-Temporal Instance Learning: Action Tubes from Class Supervision

no code implementations8 Jul 2018 Pascal Mettes, Cees G. M. Snoek

Rather than disconnecting the spatio-temporal learning from the training, we propose Spatio-Temporal Instance Learning, which enables action localization directly from box proposals in video frames.

Multiple Instance Learning Spatio-Temporal Action Localization +1

Pointly-Supervised Action Localization

no code implementations29 May 2018 Pascal Mettes, Cees G. M. Snoek

Experimental evaluation on three action localization datasets shows our pointly-supervised approach (i) is as effective as traditional box-supervision at a fraction of the annotation cost, (ii) is robust to sparse and noisy point annotations, (iii) benefits from pseudo-points during inference, and (iv) outperforms recent weakly-supervised alternatives.

Action Localization Multiple Instance Learning +1

Localizing Actions from Video Labels and Pseudo-Annotations

no code implementations28 Jul 2017 Pascal Mettes, Cees G. M. Snoek, Shih-Fu Chang

The goal of this paper is to determine the spatio-temporal location of actions in video.

Action Localization

Spot On: Action Localization from Pointly-Supervised Proposals

no code implementations26 Apr 2016 Pascal Mettes, Jan C. van Gemert, Cees G. M. Snoek

Rather than annotating boxes, we propose to annotate actions in video with points on a sparse subset of frames only.

Action Localization Multiple Instance Learning +1

The ImageNet Shuffle: Reorganized Pre-training for Video Event Detection

no code implementations23 Feb 2016 Pascal Mettes, Dennis C. Koelma, Cees G. M. Snoek

To deal with the problems of over-specific classes and classes with few images, we introduce a bottom-up and top-down approach for reorganization of the ImageNet hierarchy based on all its 21, 814 classes and more than 14 million images.

Event Detection Object Recognition

Water Detection through Spatio-Temporal Invariant Descriptors

no code implementations2 Nov 2015 Pascal Mettes, Robby T. Tan, Remco C. Veltkamp

Experimental evaluation on the Video Water Database and the DynTex database indicates the effectiveness of the proposed algorithm, outperforming multiple algorithms for dynamic texture recognition and material recognition by ca.

Dynamic Texture Recognition Material Recognition

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