Learning to Navigate for Fine-grained Classification

ECCV 2018 Ze YangTiange LuoDong WangZhiqiang HuJun GaoLiwei Wang

Fine-grained classification is challenging due to the difficulty of finding discriminative features. Finding those subtle traits that fully characterize the object is not straightforward... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Fine-Grained Image Classification CUB-200-2011 NTS-Net (K = 4) Accuracy 87.5% # 19
Fine-Grained Image Classification FGVC Aircraft NTS-Net (K=4) Accuracy 91.4% # 18
Fine-Grained Image Classification Stanford Cars NTS-Net (K=4) Accuracy 93.9% # 14

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