Boosted multi-task learning for face verification with applications to web image and video search

By Xiaogang Wang, Cha Zhang, Zhengyou Zhang. 2009

130 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

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In Computer Vision and Pattern Recognition

Citations in the corpus

An Overview of Multi-task Learning (2018, background): “Specifically, applications of MTL based on facial images include face verification [84], personalized age estimation [85], multi-cue face recognition [86], head-pose estimation [22,87], facial landmark detection [18], and facial image rotation [88].”
A Survey on Multi-Task Learning (2017, methodology): “In [146], a boosted multi-task method is proposed for face verification where different tasks share base learners in the boosting method.”
Multi-Task Boosting by Exploiting Task Relationships (2012, background): “This calls for combining boosting and multi-task learning [19, 20].”
Feature-based transfer learning with real-world applications (2010, background): “Applications of transfer learning in these fields include image classification [202, 158, 185, 218, 161, 94, 177], image retrieval [73, 115, 38], face verification from images [196], age estimation from facial images [225], image semantic segmentation [190], video retrieval [208, 73], video concept ”
Face recognition in unconstrained videos with matched background similarity (2011, background): “learning for face verification with applications to web image and video search’ [49] briefly touch on the problem of face-verification from web-videos.”
On Better Exploring and Exploiting Task Relationships in Multitask Learning: Joint Model and Feature Learning (2018, background): “Consider the merits of multi-task learning, it has been applied to various research areas, for example, web image search [1], video tracking [2], disease prediction [3], and relative attributes learning [4].”
Boosting for transfer learning with multiple sources (2010, background): “Some related work has extended boosting for multi-task learning [26] and on-line incremental learning [12].”
Online Multi-Task Learning Framework for Ensemble Forecasting (2017, unknown): “Multi-task learning has been successfully used to solve multiple related learning problems in many applications, including computer vision [6], [7], healthcare [8], [9], recommender systems [10], [11], natural language processing [12] and genomics [13].”
Multi-task Sparse Structure Learning with Gaussian Copula Models (2016, methodology): “Meanwhile MTL has been applied to problems ranging from object detection in computer vision, going through web image and video search (Wang et al., 2009), and achieving multiple microarray data set integration in computational biology (Widmer and Rätsch, 2012).”
Learning active facial patches for expression analysis (2012, background): “These features have been proven to be a powerful descriptor in expression recognition [16] and face verification [24].”
Multi-task learning for boosting with application to web search ranking (2010, background): “Related to our work, but fundamentally different, is multitask boosting for face verification [17].”
Regularized Multitask Learning for Multidimensional Log-Density Gradient Estimation (2014, unknown): “, 2008) and face verification (Wang et al., 2009).”