9 citations · 22 across the 6 of their papers we have counts for
5 papers · 1 filter
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…
ARIN: Adaptive Resampling and Instance Normalization for Robust Blind Inpainting of Dunhuang Cave Paintings
Alexander Schmidt, Prathmesh Madhu, Andreas Maier +2
Image enhancement algorithms are very useful for real world computer vision tasks where image resolution is often physically limited by the sensor size. While state-of-the-art deep…
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…
Understanding Compositional Structures in Art Historical Images using Pose and Gaze Priors
Prathmesh Madhu, Tilman Marquart, Ronak Kosti +3
Image compositions as a tool for analysis of artworks is of extreme significance for art historians. These compositions are useful in analyzing the interactions in an image to stud…
Recognizing Characters in Art History Using Deep Learning
Prathmesh Madhu, Ronak Kosti, Lara Mührenberg +3
In the field of Art History, images of artworks and their contexts are core to understanding the underlying semantic information. However, the highly complex and sophisticated repr…