SW_YoloX_det: YoloX 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_det

Description:

Shift Window-YOLOX (SW-YOLOX) incorporates a novel Shift Window-Path Aggregation Feature Pyramid Network (SW-PAFPN) to integrate with the YOLOX detector, further enhancing feature extraction and the robustness of pedestrian detection.

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:

June 23, 2023 (5 months ago)

Published:

July 03, 2023 at 11:24:27 CET

Submissions:

2

Project page / code:

n/a

Open source:

No

Hardware:

2.4 GHZ,24 Core

Runtime:

12.6 Hz

Benchmark performance:

Sequence AP MODA MODP FAF TP FP FN Rcll Prcn F1
MOT17Det0.9086.483.01.0105,0826,0829,48291.794.593.1

Detailed performance:

Sequence AP MODA MODP FAF TP FP FN Rcll Prcn F1
MOT17-010.7369.383.20.83,22634194077.490.483.4
MOT17-030.9094.683.32.267,6863,27443699.495.497.3
MOT17-060.7272.081.10.66,9736711,77679.791.285.1
MOT17-070.9090.082.80.88,70937655194.095.994.9
MOT17-080.9182.286.01.45,60788613897.686.491.6
MOT17-120.8278.885.20.24,47122392382.995.288.6
MOT17-140.6361.779.70.48,4103114,71864.196.477.0

Raw data:


SW_YoloX_det