PEPL refines pseudo-labels via CAM-based semantic estimation in two phases to reach state-of-the-art accuracy in semi-supervised fine-grained image classification.
Learning attentive pairwise interaction for fine-grained classification,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2024 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
PEPL: Precision-Enhanced Pseudo-Labeling for Fine-Grained Image Classification in Semi-Supervised Learning
PEPL refines pseudo-labels via CAM-based semantic estimation in two phases to reach state-of-the-art accuracy in semi-supervised fine-grained image classification.