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Found 3 papers, 1 papers with code
Dining on Details: LLM-Guided Expert Networks for Fine-Grained Food Recognition
Trained through an end-to-end multi-task learning process, this method enhances performance in the fine-grained food recognition task, showing exceptional prowess with highly similar classes.
Ranked #4 on
Fine-Grained Image Classification
on Food-101
Fine-Grained Image Classification
Fine-Grained Image Recognition
+2
All4One: Symbiotic Neighbour Contrastive Learning via Self-Attention and Redundancy Reduction
Nearest neighbour based methods have proved to be one of the most successful self-supervised learning (SSL) approaches due to their high generalization capabilities.
ELFIS: Expert Learning for Fine-grained Image Recognition Using Subsets
Extensive experimentation shows improvements in the SoTA FGVR benchmarks of up to +1. 3% of accuracy using both CNNs and transformer-based networks.
Fine-Grained Image Recognition
Fine-Grained Visual Recognition
