1 citations · 3 across the 4 of their papers we have counts for
5 papers
Optimizing CLIP Models for Image Retrieval with Maintained Joint-Embedding Alignment
Konstantin Schall, Kai Uwe Barthel, Nico Hezel +1
Contrastive Language and Image Pairing (CLIP), a transformative method in multimedia retrieval, typically trains two neural networks concurrently to generate joint embeddings for t…
Improved Evaluation and Generation of Grid Layouts using Distance Preservation Quality and Linear Assignment Sorting
Kai Uwe Barthel, Nico Hezel, Klaus Jung +1
Images sorted by similarity enables more images to be viewed simultaneously, and can be very useful for stock photo agencies or e-commerce applications. Visually sorted grid layout…
Real-Time Visual Navigation in Huge Image Sets Using Similarity Graphs
Kai Uwe Barthel, Nico Hezel, Konstantin Schall +1
Nowadays stock photo agencies often have millions of images. Non-stop viewing of 20 million images at a speed of 10 images per second would take more than three weeks. This demonst…
Deep Metric Learning using Similarities from Nonlinear Rank Approximations
Konstantin Schall, Kai Uwe Barthel, Nico Hezel +1
In recent years, deep metric learning has achieved promising results in learning high dimensional semantic feature embeddings where the spatial relationships of the feature vectors…
Deep Aggregation of Regional Convolutional Activations for Content Based Image Retrieval
Konstantin Schall, Kai Uwe Barthel, Nico Hezel +1
One of the key challenges of deep learning based image retrieval remains in aggregating convolutional activations into one highly representative feature vector. Ideally, this descr…