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Walk and Learn: Facial Attribute Representation Learning from Egocentric
  Video and Contextual Data

Walk and Learn: Facial Attribute Representation Learning from Egocentric Video and Contextual Data

21 April 2016
Jing Wang
Yu Cheng
Rogerio Feris
    EgoV
    CVBM
ArXivPDFHTML

Papers citing "Walk and Learn: Facial Attribute Representation Learning from Egocentric Video and Contextual Data"

18 / 18 papers shown
Title
Learning a Dynamic Map of Visual Appearance
Learning a Dynamic Map of Visual Appearance
Tawfiq Salem
Scott Workman
Nathan Jacobs
3DH
24
26
0
29 Dec 2020
Learning to Branch for Multi-Task Learning
Learning to Branch for Multi-Task Learning
Pengsheng Guo
Chen-Yu Lee
Daniel Ulbricht
18
174
0
02 Jun 2020
Hierarchical Feature Embedding for Attribute Recognition
Hierarchical Feature Embedding for Attribute Recognition
Jie Yang
Jiarou Fan
Yiru Wang
Yige Wang
Weihao Gan
Lin Liu
Wei Wu
CVBM
22
42
0
23 May 2020
Multi-Task Learning for Dense Prediction Tasks: A Survey
Multi-Task Learning for Dense Prediction Tasks: A Survey
Simon Vandenhende
Stamatios Georgoulis
Wouter Van Gansbeke
M. Proesmans
Dengxin Dai
Luc Van Gool
CVBM
24
72
0
28 Apr 2020
Aesthetic Image Captioning From Weakly-Labelled Photographs
Aesthetic Image Captioning From Weakly-Labelled Photographs
Koustav Ghosal
A. Rana
A. Smolic
24
25
0
29 Aug 2019
Transferability and Hardness of Supervised Classification Tasks
Transferability and Hardness of Supervised Classification Tasks
Anh Tran
Cuong V Nguyen
Tal Hassner
134
164
0
21 Aug 2019
Mixed-Supervised Dual-Network for Medical Image Segmentation
Mixed-Supervised Dual-Network for Medical Image Segmentation
Duo Wang
Ming Li
N. Ben-Shlomo
C. Corrales
Yu Cheng
Tao Zhang
J. Jayender
16
28
0
24 Jul 2019
Registration-free Face-SSD: Single shot analysis of smiles, facial
  attributes, and affect in the wild
Registration-free Face-SSD: Single shot analysis of smiles, facial attributes, and affect in the wild
Youngkyoon Jang
Hatice Gunes
Ioannis Patras
CVBM
16
46
0
11 Feb 2019
Attributes as Operators: Factorizing Unseen Attribute-Object
  Compositions
Attributes as Operators: Factorizing Unseen Attribute-Object Compositions
Tushar Nagarajan
Kristen Grauman
OCL
CoGe
11
59
0
27 Mar 2018
Residual Codean Autoencoder for Facial Attribute Analysis
Residual Codean Autoencoder for Facial Attribute Analysis
Akshay Sethi
Maneet Singh
Richa Singh
Mayank Vatsa
CVBM
14
19
0
20 Mar 2018
Recent Advances in Zero-shot Recognition
Recent Advances in Zero-shot Recognition
Yanwei Fu
Tao Xiang
Yu-Gang Jiang
Xiangyang Xue
Leonid Sigal
S. Gong
BDL
VLM
16
175
0
13 Oct 2017
Automatic Curation of Golf Highlights using Multimodal Excitement
  Features
Automatic Curation of Golf Highlights using Multimodal Excitement Features
Michele Merler
D. Joshi
Q. Nguyen
Stephen Hammer
John Kent
John R. Smith
Rogerio Feris
VGen
20
18
0
22 Jul 2017
Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised
  Object and Action Localization
Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization
Krishna Kumar Singh
Yong Jae Lee
22
676
0
13 Apr 2017
AFFACT - Alignment-Free Facial Attribute Classification Technique
AFFACT - Alignment-Free Facial Attribute Classification Technique
Manuel Günther
Andras Rozsa
Terrance E. Boult
CVBM
19
56
0
18 Nov 2016
Fully-adaptive Feature Sharing in Multi-Task Networks with Applications
  in Person Attribute Classification
Fully-adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification
Y. Lu
Abhishek Kumar
Shuangfei Zhai
Yu Cheng
T. Javidi
Rogerio Feris
3DH
21
384
0
16 Nov 2016
An All-In-One Convolutional Neural Network for Face Analysis
An All-In-One Convolutional Neural Network for Face Analysis
Rajeev Ranjan
S. Sankaranarayanan
Carlos D. Castillo
Rama Chellappa
CVBM
126
428
0
03 Nov 2016
A Recurrent Encoder-Decoder Network for Sequential Face Alignment
A Recurrent Encoder-Decoder Network for Sequential Face Alignment
Xi Peng
Rogerio Feris
Xiaoyu Wang
Dimitris N. Metaxas
CVBM
180
140
0
19 Aug 2016
Deeply learned face representations are sparse, selective, and robust
Deeply learned face representations are sparse, selective, and robust
Yi Sun
Xiaogang Wang
Xiaoou Tang
CVBM
250
921
0
03 Dec 2014
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