Attribute-Aware Attention Model for Fine-grained Representation Learning

2 Jan 2019Kai HanJianyuan GuoChao ZhangMingjian Zhu

How to learn a discriminative fine-grained representation is a key point in many computer vision applications, such as person re-identification, fine-grained classification, fine-grained image retrieval, etc. Most of the previous methods focus on learning metrics or ensemble to derive better global representation, which are usually lack of local information... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Fine-Grained Image Classification CompCars A3M Accuracy 95.4% # 1
Fine-Grained Image Classification CUB-200-2011 A3M Accuracy 86.2% # 24
Person Re-Identification Market-1501 A3M Rank-1 86.54 # 32
MAP 68.97 # 40

Methods used in the Paper


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