
Current open-vocabulary object detectors struggle to accurately capture and distinguish fine-grained object details like color, material, pattern, and transparency.


coremsg

evaluating-open-vocabulary-object-detectors-ability-to-discern-fine-grained-object-properties


Evaluating Open-Vocabulary Object Detectors' Ability to Discern Fine-Grained Object Properties


title_rewrite


The authors propose a novel framework, Retrieval-Augmented Losses and visual Features (RALF), that retrieves vocabularies and concepts from a large vocabulary set and augments losses and visual features to improve the generalizability of open-vocabulary object detectors.


retrieval-augmented-losses-and-visual-features-for-improved-open-vocabulary-object-detection


Retrieval-Augmented Losses and Visual Features for Improved Open-Vocabulary Object Detection
