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Architecture Search of Dynamic Cells for Semantic Video Segmentation
2020 IEEE Winter Conference on Applications of Computer Vision (WACV)
Year: 2020 | Conference Paper |
Cited by: Papers (11)
In semantic video segmentation the goal is to acquire consistent dense semantic labelling across image frames. To this end, recent approaches have been reliant on manually arranged operations applied on top of static semantic segmentation networks - with the most prominent building block being the optical flow able to provide information about scene dynamics. Related to that is the line of researc...Show More
Template-Based Automatic Search of Compact Semantic Segmentation Architectures
2020 IEEE Winter Conference on Applications of Computer Vision (WACV)
Year: 2020 | Conference Paper |
Cited by: Papers (7)
Automatic search of neural architectures for various vision and natural language tasks is becoming a prominent tool as it allows to discover high-performing structures on any dataset of interest. Nevertheless, on more difficult domains, such as dense per-pixel classification, current automatic approaches are limited in their scope - due to their strong reliance on existing image classifiers they t...Show More
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2019 | Conference Paper |
Cited by: Papers (100)
Automated design of neural network architectures tailored for a specific task is an extremely promising, albeit inherently difficult, avenue to explore. While most results in this domain have been achieved on image classification and language modelling problems, here we concentrate on dense per-pixel tasks, in particular, semantic image segmentation using fully convolutional networks. In contrast ...Show More
Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations
Vladimir Nekrasov;Thanuja Dharmasiri;Andrew Spek;Tom Drummond;Chunhua Shen;Ian Reid
2019 International Conference on Robotics and Automation (ICRA)
Year: 2019 | Conference Paper |
Cited by: Papers (66)
Deployment of deep learning models in robotics as sensory information extractors can be a daunting task to handle, even using generic GPU cards. Here, we address three of its most prominent hurdles, namely, i) the adaptation of a single model to perform multiple tasks at once (in this work, we consider depth estimation and semantic segmentation crucial for acquiring geometric and semantic understa...Show More
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