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A model is proposed in this paper which uses Convolutional Block Attention Module to select more discriminate feature and refinement residual learning to learn ...
Abstract—Human parsing is thought as a specific image se- mantic segmentation task. Most existing methods adopt encoder- decoder framework, and make full ...
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With the rise of graph model, researchers realized that attention mechanism is able to establish the correlation between graph model nodes. For example ...
Targeting at improving feature representations from multi-domain annotations more efficiently, in this thesis, we propose a novel GRAph PYramid Mutual Learning ...
Apr 9, 2023 · It is a general training scheme that effectively incorporates prior knowledge of human body parts into the representation learning process of a ...
Nov 20, 2019 · A complete guide to attention models and attention mechanisms in deep learning. Learn how to implement an attention model in python using ...
This paper investigates diverse face recognition methodologies within centralized computer vision systems, encompassing traditional techniques, deep learning ...
An attention-based model is proposed to softly weight the multi-scale features at each pixel location and deal with the multi-scale problem in the human parsing.
The studies related to the human parsing problem can be divided into three groups: probabilistic graph-based methods, general methods based on deep learning and ...
This paper proposes a trainable graph reasoning method that establishes internal structural connections between graph nodes to correct two typical errors in ...