15 citations · 59 across the 15 of their papers we have counts for
12 papers · 1 filter
Integrating Information Theory and Adversarial Learning for Cross-modal Retrieval
Wei Chen, Yu Liu, Erwin M. Bakker +1
Accurately matching visual and textual data in cross-modal retrieval has been widely studied in the multimedia community. To address these challenges posited by the heterogeneity g…
Lifelong Person Re-Identification via Adaptive Knowledge Accumulation
Nan Pu, Wei Chen, Yu Liu +2
Person ReID methods always learn through a stationary domain that is fixed by the choice of a given dataset. In many contexts (e.g., lifelong learning), those methods are ineffecti…
Preprint: Norm Loss: An efficient yet effective regularization method for deep neural networks
Theodoros Georgiou, Sebastian Schmitt, Thomas Bäck +2
Convolutional neural network training can suffer from diverse issues like exploding or vanishing gradients, scaling-based weight space symmetry and covariant-shift. In order to add…
PREPRINT: Comparison of deep learning and hand crafted features for mining simulation data
Theodoros Georgiou, Sebastian Schmitt, Thomas Bäck +3
Computational Fluid Dynamics (CFD) simulations are a very important tool for many industrial applications, such as aerodynamic optimization of engineering designs like cars shapes,…
Deep Learning for Instance Retrieval: A Survey
Wei Chen, Yu Liu, Weiping Wang +5
In recent years a vast amount of visual content has been generated and shared from many fields, such as social media platforms, medical imaging, and robotics. This abundance of con…
New Ideas and Trends in Deep Multimodal Content Understanding: A Review
Wei Chen, Weiping Wang, Li Liu +1
The focus of this survey is on the analysis of two modalities of multimodal deep learning: image and text. Unlike classic reviews of deep learning where monomodal image classifiers…