270 citations · 270 across the 6 of their papers we have counts for
6 papers
Zero-Shot Visual Classification with Guided Cropping
Piyapat Saranrittichai, Mauricio Munoz, Volker Fischer +1
Pretrained vision-language models, such as CLIP, show promising zero-shot performance across a wide variety of datasets. For closed-set classification tasks, however, there is an i…
Multi-Attribute Open Set Recognition
Piyapat Saranrittichai, Chaithanya Kumar Mummadi, Claudia Blaiotta +2
Open Set Recognition (OSR) extends image classification to an open-world setting, by simultaneously classifying known classes and identifying unknown ones. While conventional OSR a…
Overcoming Shortcut Learning in a Target Domain by Generalizing Basic Visual Factors from a Source Domain
Piyapat Saranrittichai, Chaithanya Kumar Mummadi, Claudia Blaiotta +2
Shortcut learning occurs when a deep neural network overly relies on spurious correlations in the training dataset in order to solve downstream tasks. Prior works have shown how th…
Contrasting quadratic assignments for set-based representation learning
Artem Moskalev, Ivan Sosnovik, Volker Fischer +1
The standard approach to contrastive learning is to maximize the agreement between different views of the data. The views are ordered in pairs, such that they are either positive,…
DiagViB-6: A Diagnostic Benchmark Suite for Vision Models in the Presence of Shortcut and Generalization Opportunities
Elias Eulig, Piyapat Saranrittichai, Chaithanya Kumar Mummadi +4
Common deep neural networks (DNNs) for image classification have been shown to rely on shortcut opportunities (SO) in the form of predictive and easy-to-represent visual factors. T…
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks
Fabian B. Fuchs, Daniel E. Worrall, Volker Fischer +1
We introduce the SE(3)-Transformer, a variant of the self-attention module for 3D point clouds and graphs, which is equivariant under continuous 3D roto-translations. Equivariance…