Hotel Recognition via Latent Image Embedding
arXiv:2106.08042v1Has Code
AI Analysis
This is an incremental improvement for hotel recognition systems.
The paper tackles hotel recognition by proposing Contrastive-Triplet loss, a modification to Contrastive loss, and demonstrates it achieves better retrieval on the Hotels-50K dataset.
We approach the problem of hotel recognition with deep metric learning. We overview the existing approaches and propose a modification to Contrastive loss called Contrastive-Triplet loss. We construct a robust pipeline for benchmarking metric learning models and perform experiments on Hotels-50K and CUB200 datasets. Contrastive-Triplet loss is shown to achieve better retrieval on Hotels-50k. We open-source our code.