activity
20172023
most citedUnsharp Mask Guided Filtering

51 citations · 68 across the 11 of their papers we have counts for

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13 papers · 1 filter

cs.CV2022

Less than Few: Self-Shot Video Instance Segmentation

Pengwan Yang, Yuki M. Asano, Pascal Mettes +1

The goal of this paper is to bypass the need for labelled examples in few-shot video understanding at run time. While proven effective, in many practical video settings even labell…

cs.CV20212 cited

Diagnosing Errors in Video Relation Detectors

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…

cs.CV2021

Social Fabric: Tubelet Compositions for Video Relation Detection

Shuo Chen, Zenglin Shi, Pascal Mettes +1

This paper strives to classify and detect the relationship between object tubelets appearing within a video as a <subject-predicate-object> triplet. Where existing works treat obje…

cs.CV202151 cited

Unsharp Mask Guided Filtering

Zenglin Shi, Yunlu Chen, Efstratios Gavves +2

The goal of this paper is guided image filtering, which emphasizes the importance of structure transfer during filtering by means of an additional guidance image. Where classical g…

cs.CV2021

Object Priors for Classifying and Localizing Unseen Actions

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. Where existing work relies on transf…

cs.CV20201 cited

Localizing the Common Action Among a Few Videos

Pengwan Yang, Vincent Tao Hu, Pascal Mettes +1

This paper strives to localize the temporal extent of an action in a long untrimmed video. Where existing work leverages many examples with their start, their ending, and/or the cl…