Name
Title | ||
|---|---|---|
Beyond Intra-modality Discrepancy: A Comprehensive Survey of Heterogeneous Person Re-identification. |
Abstract | ||
|---|---|---|
An effective and efficient person re-identification (ReID) algorithm will alleviate painful video watching, and accelerate the investigation progress. Recently, with the explosive requirements of practical applications, a lot of research efforts have been dedicated to heterogeneous person re-identification (He-ReID). In this paper, we review the state-of-the-art methods comprehensively with respect to four main application scenarios -- low-resolution, infrared, sketch and text. We begin with a comparison between He-ReID and the general Homogeneous ReID (Ho-ReID) task. Then, we survey the models that have been widely employed in He-ReID. Available existing datasets for performing evaluation are briefly described. We then summarize and compare the representative approaches. Finally, we discuss some future research directions. |
Year | Venue | DocType |
|---|---|---|
2019 | arXiv: Computer Vision and Pattern Recognition | Journal |
Volume | Citations | PageRank |
abs/1905.10048 | 1 | 0.35 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zheng Wang | 1 | 352 | 36.33 |
| Zhixiang Wang | 2 | 4 | 1.44 |
| Yang Wu | 3 | 9 | 11.89 |
| Jingdong Wang | 4 | 2 | 2.43 |
| Shin'ichi Satoh | 5 | 2093 | 277.41 |