Accueil Actualités Articles de recherche récents Tutoriels Ensembles de données Wiki SOTA Modèles LLM Classement GPU Événements

Français

Image Retrieval On Oxf5K

Métriques

MAP

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	MAP	Paper Title	Repository
IsoMap [32]	77.9%	Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval
Offline Diffusion	96.2%	Efficient Image Retrieval via Decoupling Diffusion into Online and Offline Processing
DIR+QE*	89%	Deep Image Retrieval: Learning global representations for image search
DELF+FT+ATT	83.8%	Large-Scale Image Retrieval with Attentive Deep Local Features
PCA [51]	82.6%	Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval
SIFT+IME layer	62.2%	Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval
LLE [33]	51.7%	Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval
DELF+FT+ATT+DIR+QE	90.0%	Large-Scale Image Retrieval with Attentive Deep Local Features
IME	83.5%	Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval
CNN+IME layer	92%	Iterative Manifold Embedding Layer Learned by Incomplete Data for Large-scale Image Retrieval
siaMAC+QE*	82.9%	CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples

0 of 11 row(s) selected.