most citedAttention Consistency on Visual Corruptions for Single-Source Domain Generalization

3 citations · 11 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV20222 cited

Distilling Knowledge from Self-Supervised Teacher by Embedding Graph Alignment

Yuchen Ma, Yanbei Chen, Zeynep Akata

Recent advances have indicated the strengths of self-supervised pre-training for improving representation learning on downstream tasks. Existing works often utilize self-supervised…

cs.CV20223 cited

Cross-Modal Fusion Distillation for Fine-Grained Sketch-Based Image Retrieval

Abhra Chaudhuri, Massimiliano Mancini, Yanbei Chen +2

Representation learning for sketch-based image retrieval has mostly been tackled by learning embeddings that discard modality-specific information. As instances from different moda…

cs.CV20223 cited

Attention Consistency on Visual Corruptions for Single-Source Domain Generalization

Ilke Cugu, Massimiliano Mancini, Yanbei Chen +1

Generalizing visual recognition models trained on a single distribution to unseen input distributions (i.e. domains) requires making them robust to superfluous correlations in the…

cs.CV20223 cited

Probabilistic Compositional Embeddings for Multimodal Image Retrieval

Andrei Neculai, Yanbei Chen, Zeynep Akata

Existing works in image retrieval often consider retrieving images with one or two query inputs, which do not generalize to multiple queries. In this work, we investigate a more ch…

cs.CV2021

Robustness via Uncertainty-aware Cycle Consistency

Uddeshya Upadhyay, Yanbei Chen, Zeynep Akata

Unpaired image-to-image translation refers to learning inter-image-domain mapping without corresponding image pairs. Existing methods learn deterministic mappings without explicitl…

cs.CV2021

Uncertainty-Guided Progressive GANs for Medical Image Translation

Uddeshya Upadhyay, Yanbei Chen, Tobias Hepp +2

Image-to-image translation plays a vital role in tackling various medical imaging tasks such as attenuation correction, motion correction, undersampled reconstruction, and denoisin…