|
Alias
|
Ref.
|
Name
|
Person part
|
Localization
|
Age
|
Gender
|
Implementation
|
Count performance
|
Speed
|
|---|
| | | | |
Detection
|
Tracking
| | |
GPU
|
CPU
|
Instantaneous
|
Cumulative
| |
|---|
| | | | | | | | | | |
People
|
OTS
| | |
|---|
|
A1
|
[14]
|
RetinaFace
|
Face
|
\(\checkmark\)
| | | |
\(\checkmark\)
|
\(\checkmark\)
|
+
|
+++
|
+
|
+++
|
|
A2
|
[15]
|
MTCNN
|
Face
|
\(\checkmark\)
| | | |
\(\checkmark\)
|
\(\checkmark\)
|
+
|
+++
|
+
|
+++
|
|
A3
|
[16]
|
DeepSORT
|
Person
| |
\(\checkmark\)
| | |
\(\checkmark\)
|
\(\checkmark\)
|
+++
|
+
|
+++
|
++
|
|
A4
|
[17]
|
TRMOT
|
Person
| |
\(\checkmark\)
| | |
\(\checkmark\)
| |
+++
|
+
|
+++
|
++
|
|
A5
|
[18]
|
FaceLib
|
Face
|
–
|
–
|
\(\checkmark\)
|
\(\checkmark\)
|
\(\checkmark\)
|
\(\checkmark\)
|
–
|
–
|
–
|
+++
|
|
A6
|
[19]
|
DEX
|
Face
|
–
| |
\(\checkmark\)
|
\(\checkmark\)
|
\(\checkmark\)
|
\(\checkmark\)
|
–
|
–
|
–
|
+++
|
|
C1
|
Commercial-1
|
Face
| |
\(\checkmark\)
|
\(\checkmark\)
|
\(\checkmark\)
| |
\(\checkmark\)
|
+
|
+++
|
+++
|
++
|
|
C2
|
Commercial-2
|
Face
| |
\(\checkmark\)
|
\(\checkmark\)
|
\(\checkmark\)
| |
\(\checkmark\)
|
+++
|
+++
|
+++
|
++
|
- Algorithms count performance and speed are assessed, on a scale from 1 to 3 (the higher, the better) and regardless of the system used, based on generic algorithmic concepts (e.g., tracking outperforms detection for cumulative counts) and not on experimental results. OTS: opportunity to see. A4 was not compatible with OpenVINO optimization at submission time, thus we run A4 on CPU without optimization
