Maximum-Entropy Fine Grained Classification

NeurIPS 2018 Abhimanyu DubeyOtkrist GuptaRamesh RaskarNikhil Naik

Fine-Grained Visual Classification (FGVC) is an important computer vision problem that involves small diversity within the different classes, and often requires expert annotators to collect data. Utilizing this notion of small visual diversity, we revisit Maximum-Entropy learning in the context of fine-grained classification, and provide a training routine that maximizes the entropy of the output probability distribution for training convolutional neural networks on FGVC tasks... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK LEADERBOARD
Fine-Grained Image Classification NABirds MaxEnt-CNN Accuracy 83.0% # 6