9 citations · 9 across the 4 of their papers we have counts for
5 papers · 1 filter
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…
Adapt Everywhere: Unsupervised Adaptation of Point-Clouds and Entropy Minimisation for Multi-modal Cardiac Image Segmentation
Sulaiman Vesal, Mingxuan Gu, Ronak Kosti +2
Deep learning models are sensitive to domain shift phenomena. A model trained on images from one domain cannot generalise well when tested on images from a different domain, despit…
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…
Context Based Emotion Recognition using EMOTIC Dataset
Ronak Kosti, Jose M. Alvarez, Adria Recasens +1
In our everyday lives and social interactions we often try to perceive the emotional states of people. There has been a lot of research in providing machines with a similar capacit…