929 citations · 1.3k across the 24 of their papers we have counts for
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Personalized and Occupational-aware Age Progression by Generative Adversarial Networks
Siyu Zhou, Weiqiang Zhao, Jiashi Feng +4
Face age progression, which aims to predict the future looks, is important for various applications and has been received considerable attentions. Existing methods and datasets are…
HashGAN:Attention-aware Deep Adversarial Hashing for Cross Modal Retrieval
Xi Zhang, Siyu Zhou, Jiashi Feng +5
As the rapid growth of multi-modal data, hashing methods for cross-modal retrieval have received considerable attention. Deep-networks-based cross-modal hashing methods are appeali…
Transductive Zero-Shot Hashing via Coarse-to-Fine Similarity Mining
Hanjiang Lai, Yan Pan
Zero-shot Hashing (ZSH) is to learn hashing models for novel/target classes without training data, which is an important and challenging problem. Most existing ZSH approaches explo…
Improved Search in Hamming Space using Deep Multi-Index Hashing
Hanjiang Lai, Yan Pan
Similarity-preserving hashing is a widely-used method for nearest neighbour search in large-scale image retrieval tasks. There has been considerable research on generating efficien…
Personalized Age Progression with Bi-level Aging Dictionary Learning
Xiangbo Shu, Jinhui Tang, Zechao Li +3
Age progression is defined as aesthetically re-rendering the aging face at any future age for an individual face. In this work, we aim to automatically render aging faces in a pers…