7 citations · 19 across the 7 of their papers we have counts for
10 papers
Imbalance Robust Softmax for Deep Embeeding Learning
Hao Zhu, Yang Yuan, Guosheng Hu +2
Deep embedding learning is expected to learn a metric space in which features have smaller maximal intra-class distance than minimal inter-class distance. In recent years, one rese…
Off-Policy Self-Critical Training for Transformer in Visual Paragraph Generation
Shiyang Yan, Yang Hua, Neil M. Robertson
Recently, several approaches have been proposed to solve language generation problems. Transformer is currently state-of-the-art seq-to-seq model in language generation. Reinforcem…
ParaCNN: Visual Paragraph Generation via Adversarial Twin Contextual CNNs
Shiyang Yan, Yang Hua, Neil Robertson
Image description generation plays an important role in many real-world applications, such as image retrieval, automatic navigation, and disabled people support. A well-developed t…
Instance Cross Entropy for Deep Metric Learning
Xinshao Wang, Elyor Kodirov, Yang Hua +1
Loss functions play a crucial role in deep metric learning thus a variety of them have been proposed. Some supervise the learning process by pairwise or tripletwise similarity cons…
ID-aware Quality for Set-based Person Re-identification
Xinshao Wang, Elyor Kodirov, Yang Hua +1
Set-based person re-identification (SReID) is a matching problem that aims to verify whether two sets are of the same identity (ID). Existing SReID models typically generate a feat…
Derivative Manipulation for General Example Weighting
Xinshao Wang, Elyor Kodirov, Yang Hua +1
Real-world large-scale datasets usually contain noisy labels and are imbalanced. Therefore, we propose derivative manipulation (DM), a novel and general example weighting approach…