Name
Title | ||
|---|---|---|
Deep Discriminative Representation Learning For Face Verification And Person Re-Identification On Unconstrained Condition |
Abstract | ||
|---|---|---|
In this paper, we address face verification and person re-identification tasks under the unconstrained condition. Both tasks under the unconstrained condition are difficult since the testing dataset can contain the identities not appeared in training dataset. To overcome the difficulty, we propose deep discriminative representation learning (DDRL) to learn a discriminative representation which can cover not only trained representation but the appearance of images which are not trained. DDRL can be viewed as imposing discriminative constraints on the learnt representation via joint optimization for verification and identification objectives. The experimental results for face verification and person re-identification shows the superiority of DDRL in both tasks. |
Year | Venue | Keywords |
|---|---|---|
2018 | 2018 25TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | Deep discriminative representation learning, metric learning, face verification, person re-identification |
Field | DocType | ISSN |
Face verification,Task analysis,Pattern recognition,Computer science,Feature extraction,Artificial intelligence,Discriminative model,Feature learning | Conference | 1522-4880 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jongmin Yu | 1 | 9 | 4.54 |
| Donghwuy Ko | 2 | 0 | 0.34 |
| Hangyul Moon | 3 | 0 | 0.34 |
| Moongu Jeon | 4 | 456 | 72.81 |