Detection Challenge Results

Detection challenge results are presented below. The plot results of detectors can be found here.

The Precision-Recall curve of the submission can be drawn compared to the state-of-the-art detectors here.

Method Overall Easy Medium Hard Cloudy Night Rainy Sunny Speed Environment
1 RTN 74.15% 91.52% 79.16% 61.73% 77.02% 77.20% 65.27% 84.14% 19.61 fps (C++) 2x Intel Xeon E5-2620v4, RAM:128GB,GPU:GTX1080
Anonymous submission
2 EB 67.96% 89.65% 73.12% 53.64% 72.42% 73.93% 53.40% 83.73% 10.00 fps (C++) 1x GPU:TitanX
Li Wang, Yao Lu, Hong Wang, Yingbin Zheng, Hao Ye, Xiangyang Xue, Evolving Boxes for Fast Vehicle Detection. In IEEE International Conference on Multimedia and Expo (ICME), 2017.
3 NANO 63.01% 80.33% 68.04% 50.73% 67.00% 62.20% 55.89% 73.89% - -
Anonymous submission
4 FasterRCNN2 58.45% 82.75% 63.05% 44.25% 66.29% 69.85% 45.16% 62.34% 11.11 fps (C++) 1x GPU:TitanX
Anonymous submission
5 YOLO2 57.72% 83.28% 62.25% 42.44% 57.97% 64.53% 47.84% 69.75% - 2x Intel Xeon E5-2620v4, RAM:128GB,GPU:GTX1080
Anonymous submission
6 CompACT 53.23% 64.84% 58.70% 43.16% 63.23% 46.37% 44.21% 71.16% 0.22 fps (Matlab,C++) 2x Intel Xeon E5-2470v2 @2.40GHz, RAM:64GB, GPU:Tesla K40
Z. Cai, M. Saberian, and N. Vasconcelos. Learning complexity-aware cascades for deep pedestrian detection. In ICCV, 2015. [code]
7 R-CNN 48.95% 59.31% 54.06% 39.47% 59.73% 39.32% 39.06% 67.52% 0.10 fps (Matlab,C++) 2x Intel Xeon E5-2470v2 @2.40GHz, RAM:64GB, GPU:Tesla K40
R. B. Girshick, J. Donahue, T. Darrell, and J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In CVPR, pages 580-587, 2014. [code]
8 ACF 46.35% 54.27% 51.52% 38.07% 58.30% 35.29% 37.09% 66.58% 0.67 fps (Matlab,C++) 2x Intel Xeon E5-2470v2 @2.40GHz, RAM:64GB
P. Dollár, R. Appel, S. Belongie, and P. Perona. Fast feature pyramids for object detection. In TPAMI, 36(8):1532-1545, 2014. [code]
9 SA-FRCNN 45.83% 73.93% 49.00% 30.76% 49.97% 52.30% 33.39% 55.04% - -
Anonymous submission
10 DPM 25.70% 34.42% 30.29% 17.62% 24.78% 30.91% 25.55% 31.77% 0.17 fps (Matlab,C++) 4x Intel Core i7-6600U @2.60GHz, RAM:8GB
P. F. Felzenszwalb, R. B. Girshick, D. A. McAllester, and D. Ramanan. Object detection with discriminatively trained part-based models. In TPAMI, 32(9):1627-1645, 2010. [code]