In this paper, we propose an autonomous information seeking visual quest...
Contrastive image-text models such as CLIP form the building blocks of m...
Retrieval augmented models are becoming increasingly popular for compute...
In this paper, we propose an end-to-end Retrieval-Augmented Visual Langu...
We study class-incremental learning, a training setup in which new class...
Recent advances in deep learning have relied on large, labelled datasets...
Real-world imagery is often characterized by a significant imbalance of ...
In this work we introduce an approach for incremental learning, which
pr...
In this work we consider the problem of learning a classifier from noisy...
Semi-supervised learning is becoming increasingly important because it c...
This work addresses approximate nearest neighbor search applied in the d...
State of the art image retrieval performance is achieved with CNN featur...
In this paper we address issues with image retrieval benchmarking on sta...
In this work we present a novel unsupervised framework for hard training...
Severe background clutter is challenging in many computer vision tasks,
...
Despite the success of deep learning on representing images for particul...
Query expansion is a popular method to improve the quality of image retr...
We study an indexing architecture to store and search in a database of
h...
We consider a pipeline for image classification or search based on codin...
We introduce ConceptVision, a method that aims for high accuracy in
cate...
Unusual events are important as being possible indicators of undesired
c...