ICCV 2019 Workshop & Challenge on Computer Vision for Wildlife Conservation (CVWC) Detection and ReID Tracks
Before we designed our model, we looked into the dataset carefully and the details are as follows:
The distribution of bounding box according to size, count and square.
We joined 3 tracks of 4 in this workshop which are detection, plain ReID and wild ReID.
The final results are:
Track | mAP(single_cam in ReID) | top-1(single_cam) | top-5(single_cam) | mAP(cross_cam) | top-1(single_cam) | top-5(cross_cam) | GFLOPs | Param |
---|---|---|---|---|---|---|---|---|
Detection | 0.60 | - | - | - | - | - | 245.3 | 45.0M |
Plain ReID | 0.84 | 0.95 | 0.99 | 0.46 | 0.87 | 0.93 | - | - |
Wild ReID | 0.82 | 0.93 | 0.96 | 0.46 | 0.84 | 0.90 | - | - |
Please refer to the respective folder for more details.