433 citations · 821 across the 11 of their papers we have counts for
12 papers · 1 filter
Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identification
Lin Wu, Yang Wang, Junbin Gao +1
Video-based person re-identification (re-id) is a central application in surveillance systems with significant concern in security. Matching persons across disjoint camera views in…
Deep Co-attention based Comparators For Relative Representation Learning in Person Re-identification
Lin Wu, Yang Wang, Junbin Gao +1
Person re-identification (re-ID) requires rapid, flexible yet discriminant representations to quickly generalize to unseen observations on-the-fly and recognize the same identity a…
Multi-View Spectral Clustering via Structured Low-Rank Matrix Factorization
Yang Wang, Lin Wu
Multi-view data clustering attracts more attention than their single view counterparts due to the fact that leveraging multiple independent and complementary information from multi…
Vectorial Dimension Reduction for Tensors Based on Bayesian Inference
Fujiao Ju, Yanfeng Sun, Junbin Gao +2
Dimensionality reduction for high-order tensors is a challenging problem. In conventional approaches, higher order tensors are `vectorized` via Tucker decomposition to obtain lower…
What-and-Where to Match: Deep Spatially Multiplicative Integration Networks for Person Re-identification
Lin Wu, Yang Wang, Xue Li +1
Matching pedestrians across disjoint camera views, known as person re-identification (re-id), is a challenging problem that is of importance to visual recognition and surveillance.…
Deep Adaptive Feature Embedding with Local Sample Distributions for Person Re-identification
Lin Wu, Yang Wang, Junbin Gao +1
Person re-identification (re-id) aims to match pedestrians observed by disjoint camera views. It attracts increasing attention in computer vision due to its importance to surveilla…