Part-based R-CNNs for Fine-grained Category Detection

15 Jul 2014 Ning Zhang Jeff Donahue Ross Girshick Trevor Darrell

Semantic part localization can facilitate fine-grained categorization by explicitly isolating subtle appearance differences associated with specific object parts. Methods for pose-normalized representations have been proposed, but generally presume bounding box annotations at test time due to the difficulty of object detection... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Fine-Grained Image Classification CUB-200-2011 Part RCNN Accuracy 76.4% # 27

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