SW_YoloX_N: YoloX-Nano with sliding Windows


Video not available.

Rendering of new sequences is currently deactivated due to heavy load.

Rendering of new sequences is currently deactivated due to heavy load.

Rendering of new sequences is currently deactivated due to heavy load.

Rendering of new sequences is currently deactivated due to heavy load.

Rendering of new sequences is currently deactivated due to heavy load.

Rendering of new sequences is currently deactivated due to heavy load.

Rendering of new sequences is currently deactivated due to heavy load.

Benchmark:

Short name:

SW_YoloX_N

Description:

A Lightweight version of Shift Window-YOLOX (SW-YOLOX)

Reference:

C.-Y. Tsai, R.-Y. Wang and Y.-C. Chiu, “SW-YOLOX: A Real-Time Pedestrian Detection System Based on Sliding Window-Mixed Attention Mechanism in YOLOX Lightweight Network,” Neurocomputing, accepted for publication, DOI: https://doi.org/10.1016/j.neucom.2024.128357

Last submitted:

July 04, 2023 (1 year ago)

Published:

July 04, 2023 at 16:20:28 CET

Submissions:

1

Project page / code:

Open source:

Yes

Hardware:

2.4 GHZ,24 Core

Runtime:

46.4 Hz

Benchmark performance:

Sequence AP MODA MODP FAF TP FP FN Rcll Prcn F1
MOT17Det0.8282.582.21.3102,0227,50212,54289.193.291.1

Detailed performance:

Sequence AP MODA MODP FAF TP FP FN Rcll Prcn F1
MOT17-010.6363.982.30.32,7831191,38366.895.978.7
MOT17-030.9191.582.73.267,1704,84095298.693.395.9
MOT17-060.8173.979.70.57,0055411,74480.192.886.0
MOT17-070.8182.081.21.08,1025131,15887.594.090.7
MOT17-080.9179.585.01.55,52095122596.185.390.4
MOT17-120.7370.983.80.23,9741511,42073.796.383.5
MOT17-140.5453.977.40.57,4683875,66056.995.171.2

Raw data:


SW_YoloX_N