1.3k citations · 3.8k across the 222 of their papers we have counts for
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Spatial Priors via Space Filling Curves for Small and Limited Data Vision Transformers
Leyla Naz Candogan, Arshia Afzal, Pol Puigdemont +1
Though Vision Transformers (ViTs) have become the dominant backbone in many computer vision tasks, due to permutation equivariance, their attention mechanism lacks explicit spatial…
Diffusion-based Cumulative Adversarial Purification for Vision Language Models
Jia Fu, Yongtao Wu, Yihang Chen +5
Vision Language Models (VLMs) have shown remarkable capabilities in multimodal understanding, yet their susceptibility to adversarial perturbations poses a significant threat to th…
The Last Mile to Supervised Performance: Semi-Supervised Domain Adaptation for Semantic Segmentation
Daniel Morales-Brotons, Grigorios Chrysos, Stratis Tzoumas +1
Supervised deep learning requires massive labeled datasets, but obtaining annotations is not always easy or possible, especially for dense tasks like semantic segmentation. To over…
Membership Inference Attacks against Large Vision-Language Models
Zhan Li, Yongtao Wu, Yihang Chen +3
Large vision-language models (VLLMs) exhibit promising capabilities for processing multi-modal tasks across various application scenarios. However, their emergence also raises sign…
Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations
Justin Deschenaux, Igor Krawczuk, Grigorios Chrysos +1
Denoising Diffusion Probabilistic Models (DDPMs) exhibit remarkable capabilities in image generation, with studies suggesting that they can generalize by composing latent factors l…
Multilinear Operator Networks
Yixin Cheng, Grigorios G. Chrysos, Markos Georgopoulos +1
Despite the remarkable capabilities of deep neural networks in image recognition, the dependence on activation functions remains a largely unexplored area and has yet to be elimina…
Evaluating the Fairness of Discriminative Foundation Models in Computer Vision
Junaid Ali, Matthaeus Kleindessner, Florian Wenzel +3
We propose a novel taxonomy for bias evaluation of discriminative foundation models, such as Contrastive Language-Pretraining (CLIP), that are used for labeling tasks. We then syst…
Regularization of polynomial networks for image recognition
Grigorios G Chrysos, Bohan Wang, Jiankang Deng +1
Deep Neural Networks (DNNs) have obtained impressive performance across tasks, however they still remain as black boxes, e.g., hard to theoretically analyze. At the same time, Poly…
Self-Supervised Neural Architecture Search for Imbalanced Datasets
Aleksandr Timofeev, Grigorios G. Chrysos, Volkan Cevher
Neural Architecture Search (NAS) provides state-of-the-art results when trained on well-curated datasets with annotated labels. However, annotating data or even having balanced num…