MAIN: Multi-Attention Instance Network for Video Segmentation

Alcázar, Juan León; Bravo, M. A.; Thabet, Ali; Jeanneret, Guillaume; Brox, Thomas; Arbeláez, Pablo; Ghanem, Bernard

doi:10.48550/arxiv.1904.05847

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Video Object Segmentation1

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2019

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“…They aim to group pixels consistent in both appearance and motion and extract the most salient spatio-temporal objects. Several techniques exploit object proposals, attention, such as [1], and optical flow. Since these methods do not have any knowledge about the object to track, they may have issues working on videos with multiple moving objects and cluttered backgrounds.…”

Section: Video Object Segmentationmentioning

confidence: 99%

Video Object Linguistic Grounding

Herrera-Palacio

Ventura

Giró-i-Nieto

2019

1st International Workshop on Multimodal Understanding and Learning for Embodied Applications

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The goal of this work is segmenting on a video sequence the objects which are mentioned in a linguistic description of the scene. We have adapted an existing deep neural network that achieves state of the art performance in semi-supervised video object segmentation, to add a linguistic branch that would generate an attention map over the video frames, making the segmentation of the objects temporally consistent along the sequence.

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Section: Video Object Segmentationmentioning

confidence: 99%