Text-guided image retrieval is to incorporate conditional text to better...
Parsing questions into executable logical forms has showed impressive re...
Multi-hop QA requires reasoning over multiple supporting facts to answer...
Few-shot learning with N-way K-shot scheme is an open challenge in machi...
Unsupervised image hashing, which maps images into binary codes without
...
Plasticity-stability dilemma is a main problem for incremental learning,...
Motivated by the following two observations: 1) people are aging differe...
Many retrieval applications can benefit from multiple modalities, e.g., ...
Fine-grained image hashing is a challenging problem due to the difficult...
Existing value-factorized based Multi-Agent deep Reinforce-ment Learning...
In recent years, deep-networks-based hashing has become a leading approa...
Virtual try-on system under arbitrary human poses has huge application
p...
Despite remarkable advances in image synthesis research, existing works ...
In this paper, we focus on triplet-based deep binary embedding networks ...
Recently, deep-networks-based hashing (deep hashing) has become a leadin...
Face age progression, which aims to predict the future looks, is importa...
As the rapid growth of multi-modal data, hashing methods for cross-modal...
Zero-shot Hashing (ZSH) is to learn hashing models for novel/target clas...
Similarity-preserving hashing is a widely-used method for nearest neighb...
Age progression is defined as aesthetically re-rendering the aging face ...
Similarity-preserving hashing is a commonly used method for nearest neig...
Similarity-preserving hashing is a widely-used method for nearest neighb...