Towards Open World Object Detection

Humans have a natural instinct to identify unknown object instances in their environments. The intrinsic curiosity about these unknown instances aids in learning about them, when the corresponding knowledge is eventually available... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Open World Object Detection COCO 2017 (Electronic, Indoor, Kitchen, Furniture) ORE MAP 26.66 # 1
Open World Object Detection COCO 2017 (Outdoor, Accessories, Appliance, Truck) ORE A-OSE 7772 # 1
WI 0.0154 # 1
MAP 38.98 # 1
Open World Object Detection COCO 2017 (Sports, Food) ORE WI 0.0081 # 1
A-OSE 6634 # 1
MAP 29.32 # 1
Open World Object Detection PASCAL VOC 2007 ORE WI 0.02193 # 1
A-OSE 8234 # 1
MAP 56.34 # 1

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet