SW_YoloX_N: YoloX-Nano with sliding Windows


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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, under review.

Last submitted:

July 04, 2023 (7 months ago)

Published:

July 04, 2023 at 16:20:28 CET

Submissions:

1

Project page / code:

n/a

Open source:

No

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