44 citations · 62 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
IMAE for Noise-Robust Learning: Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude's Variance Matters
Xinshao Wang, Yang Hua, Elyor Kodirov +2
In this work, we study robust deep learning against abnormal training data from the perspective of example weighting built in empirical loss functions, i.e., gradient magnitude wit…
Ranked List Loss for Deep Metric Learning
Xinshao Wang, Yang Hua, Elyor Kodirov +1
The objective of deep metric learning (DML) is to learn embeddings that can capture semantic similarity and dissimilarity information among data points. Existing pairwise or triple…