ArticleSensors (Basel, Switzerland)2020
A Multi-Task Framework for Facial Attributes Classification through End-to-End Face Parsing and Deep Convolutional Neural Networks.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Comparing Activation Typicality and Sparsity in a Deep CNN to Predict Facial Beauty.Computational brain & behavior · 2025Article
- Article
- Combining CNNs and Markov-like Models for Facial Landmark Detection with Spatial Consistency Estimates.Journal of imaging · 2023Article
- Face-mask-aware Facial Expression Recognition based on Face Parsing and Vision Transformer.Pattern recognition letters · 2022Article
- Advances and Trends in Real Time Visual Crowd Analysis.Sensors (Basel, Switzerland) · 2020Review
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Authors and funding
5 authors.
Funding
Abstract
Human face image analysis is an active research area within computer vision. In this paper we propose a framework for face image analysis, addressing three challenging problems of race, age, and gender recognition through face parsing. We manually labeled face images for training an end-to-end face parsing model through Deep Convolutional Neural Networks. The deep learning-based segmentation model parses a face image into seven dense classes. We use the probabilistic classification method and created probability maps for each face class. The probability maps are used as feature descriptors. We trained another Convolutional Neural Network model by extracting features from probability maps of the corresponding class for each demographic task (race, age, and gender). We perform extensive experiments on state-of-the-art datasets and obtained much better results as compared to previous results.
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Registered trials
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