11 citations · 24 across the 10 of their papers we have counts for
12 papers
Automated Goldsmith's Mark Retrieval in Silverware
Atmik Tiwari, Vincent Christlein, Mark Fichtner +5
For art historians, goldsmith marks play a critical role in the identification and dating of artifacts. In practice, experts must manually compare a query mark against hundreds of…
Lot Machine: Multimodal Lot Extraction from Auction Catalogs
Mathias Zinnen, Alisha Mund, Sabine Lang +3
For provenance research and art market studies, auction catalogs are an essential resource to trace specific objects over time and space. While historical auction catalogs follow e…
Example-based Robust Abnormality Detection with Minimal Annotations using Exemplar Med-DETR
Sheethal Bhat, Bogdan Georgescu, Awais Mansoor +5
Reducing annotation requirements remains a key challenge in developing robust medical object detectors. To address this, Vision-Language (VL) object detection methods leverage grou…
Data Augmentation via Latent Diffusion Models for Detecting Smell-Related Objects in Historical Artworks
Ahmed Sheta, Mathias Zinnen, Aline Sindel +2
Finding smell references in historic artworks is a challenging problem. Beyond artwork-specific challenges such as stylistic variations, their recognition demands exceptionally det…
Exemplar Med-DETR: Toward Generalized and Robust Lesion Detection in Mammogram Images and beyond
Sheethal Bhat, Bogdan Georgescu, Adarsh Bhandary Panambur +8
Detecting abnormalities in medical images poses unique challenges due to differences in feature representations and the intricate relationship between anatomical structures and abn…
Smelly, dense, and spreaded: The Object Detection for Olfactory References (ODOR) dataset
Mathias Zinnen, Prathmesh Madhu, Inger Leemans +6
Real-world applications of computer vision in the humanities require algorithms to be robust against artistic abstraction, peripheral objects, and subtle differences between fine-g…
Gesture Classification in Artworks Using Contextual Image Features
Azhar Hussian, Mathias Zinnen, Thi My Hang Tran +2
Recognizing gestures in artworks can add a valuable dimension to art understanding and help to acknowledge the role of the sense of smell in cultural heritage. We propose a method…
Novel Artistic Scene-Centric Datasets for Effective Transfer Learning in Fragrant Spaces
Shumei Liu, Haiting Huang, Mathias Zinnen +2
Olfaction, often overlooked in cultural heritage studies, holds profound significance in shaping human experiences and identities. Examining historical depictions of olfactory scen…
Smell and Emotion: Recognising emotions in smell-related artworks
Vishal Patoliya, Mathias Zinnen, Andreas Maier +1
Emotions and smell are underrepresented in digital art history. In this exploratory work, we show that recognising emotions from smell-related artworks is technically feasible but…
SniffyArt: The Dataset of Smelling Persons
Mathias Zinnen, Azhar Hussian, Hang Tran +3
Smell gestures play a crucial role in the investigation of past smells in the visual arts yet their automated recognition poses significant challenges. This paper introduces the Sn…
Transfer Learning for Olfactory Object Detection
Mathias Zinnen, Prathmesh Madhu, Peter Bell +2
We investigate the effect of style and category similarity in multiple datasets used for object detection pretraining. We find that including an additional stage of object-detectio…
ODOR: The ICPR2022 ODeuropa Challenge on Olfactory Object Recognition
Mathias Zinnen, Prathmesh Madhu, Ronak Kosti +3
The Odeuropa Challenge on Olfactory Object Recognition aims to foster the development of object detection in the visual arts and to promote an olfactory perspective on digital heri…