3 citations · 3 across the 5 of their papers we have counts for
5 papers
A Visual RAG Pipeline for Few-Shot Fine-Grained Product Classification
Bianca Lamm, Janis Keuper
Despite the rapid evolution of learning and computer vision algorithms, Fine-Grained Classification (FGC) still poses an open problem in many practically relevant applications. In…
Can Visual Language Models Replace OCR-Based Visual Question Answering Pipelines in Production? A Case Study in Retail
Bianca Lamm, Janis Keuper
Most production-level deployments for Visual Question Answering (VQA) tasks are still build as processing pipelines of independent steps including image pre-processing, object- and…
Can We Talk Models Into Seeing the World Differently?
Paul Gavrikov, Jovita Lukasik, Steffen Jung +4
Unlike traditional vision-only models, vision language models (VLMs) offer an intuitive way to access visual content through language prompting by combining a large language model…
Retail-786k: a Large-Scale Dataset for Visual Entity Matching
Bianca Lamm, Janis Keuper
Entity Matching (EM) defines the task of learning to group objects by transferring semantic concepts from example groups (=entities) to unseen data. Despite the general availabilit…
Fine-Grained Product Classification on Leaflet Advertisements
Daniel Ladwig, Bianca Lamm, Janis Keuper
In this paper, we describe a first publicly available fine-grained product recognition dataset based on leaflet images. Using advertisement leaflets, collected over several years f…