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Found 7 papers, 0 papers with code
Multimodal Recurrent Neural Networks with Information Transfer Layers for Indoor Scene Labeling
This paper proposes a new method called Multimodal RNNs for RGB-D scene semantic segmentation.
Joint Learning of Siamese CNNs and Temporally Constrained Metrics for Tracklet Association
Then the Siamese CNN and temporally constrained metrics are jointly learned online to construct the appearance-based tracklet affinity models.
Scene Parsing with Integration of Parametric and Non-parametric Models
The local beliefs of pixels are output by CNN-Ensemble.
Learning Contextual Dependencies with Convolutional Hierarchical Recurrent Neural Networks
In this manuscript, we integrate CNNs with HRNNs, and develop end-to-end convolutional hierarchical recurrent neural networks (C-HRNNs).
DAG-Recurrent Neural Networks For Scene Labeling
In image labeling, local representations for image units are usually generated from their surrounding image patches, thus long-range contextual information is not effectively encoded.
Ranked #19 on
Semantic Segmentation
on COCO-Stuff test
Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification
In order to encode the class correlation and class specific information in image representation, we propose a new local feature learning approach named Deep Discriminative and Shareable Feature Learning (DDSFL).
Integrating Parametric and Non-Parametric Models For Scene Labeling
We adopt Convolutional Neural Networks (CNN) as our parametric model to learn discriminative features and classifiers for local patch classification.
