Name
Abstract | ||
|---|---|---|
We introduce a detection framework for dense crowd counting and eliminate the need for the prevalent density regression paradigm. Typical counting models predict crowd density for an image as opposed to detecting every person. These regression methods, in general, fail to localize persons accurate enough for most applications other than counting. Hence, we adopt an architecture that locates every ... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TPAMI.2020.2974830 | IEEE Transactions on Pattern Analysis and Machine Intelligence |
Keywords | DocType | Volume |
Training,Detectors,Magnetic heads,Face,Feature extraction,Task analysis | Journal | 43 |
Issue | ISSN | Citations |
8 | 0162-8828 | 3 |
PageRank | References | Authors |
0.39 | 8 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| deepak babu sam | 1 | 5 | 1.09 |
| Skand Vishwanath Peri | 2 | 3 | 0.39 |
| Mukuntha Narayanan Sundararaman | 3 | 3 | 0.39 |
| Amogh Kamath | 4 | 3 | 0.39 |
| R. Venkatesh Babu | 5 | 1046 | 84.83 |