3.2k citations · 4.3k across the 27 of their papers we have counts for
13 papers · 1 filter
To Adapt or Not to Adapt? Real-Time Adaptation for Semantic Segmentation
Marc Botet Colomer, Pier Luigi Dovesi, Theodoros Panagiotakopoulos +6
The goal of Online Domain Adaptation for semantic segmentation is to handle unforeseeable domain changes that occur during deployment, like sudden weather events. However, the high…
Dense FixMatch: a simple semi-supervised learning method for pixel-wise prediction tasks
Miquel Martí i Rabadán, Alessandro Pieropan, Hossein Azizpour +1
We propose Dense FixMatch, a simple method for online semi-supervised learning of dense and structured prediction tasks combining pseudo-labeling and consistency regularization via…
PatchDropout: Economizing Vision Transformers Using Patch Dropout
Yue Liu, Christos Matsoukas, Fredrik Strand +2
Vision transformers have demonstrated the potential to outperform CNNs in a variety of vision tasks. But the computational and memory requirements of these models prohibit their us…
Towards Self-Supervised Learning of Global and Object-Centric Representations
Federico Baldassarre, Hossein Azizpour
Self-supervision allows learning meaningful representations of natural images, which usually contain one central object. How well does it transfer to multi-entity scenes? We discus…
CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer
Moein Sorkhei, Yue Liu, Hossein Azizpour +6
Interval and large invasive breast cancers, which are associated with worse prognosis than other cancers, are usually detected at a late stage due to false negative assessments of…
Explanation-based Weakly-supervised Learning of Visual Relations with Graph Networks
Federico Baldassarre, Kevin Smith, Josephine Sullivan +1
Visual relationship detection is fundamental for holistic image understanding. However, the localization and classification of (subject, predicate, object) triplets remain challeng…
Hyperplane Arrangements of Trained ConvNets Are Biased
Matteo Gamba, Stefan Carlsson, Hossein Azizpour +1
We investigate the geometric properties of the functions learned by trained ConvNets in the preactivation space of their convolutional layers, by performing an empirical study of h…
GANtruth - an unpaired image-to-image translation method for driving scenarios
Sebastian Bujwid, Miquel Martí, Hossein Azizpour +1
Synthetic image translation has significant potentials in autonomous transportation systems. That is due to the expense of data collection and annotation as well as the unmanageabl…
Spotlight the Negatives: A Generalized Discriminative Latent Model
Hossein Azizpour, Mostafa Arefiyan, Sobhan Naderi Parizi +1
Discriminative latent variable models (LVM) are frequently applied to various visual recognition tasks. In these systems the latent (hidden) variables provide a formalism for model…
Persistent Evidence of Local Image Properties in Generic ConvNets
Ali Sharif Razavian, Hossein Azizpour, Atsuto Maki +3
Supervised training of a convolutional network for object classification should make explicit any information related to the class of objects and disregard any auxiliary informatio…
Factors of Transferability for a Generic ConvNet Representation
Hossein Azizpour, Ali Sharif Razavian, Josephine Sullivan +2
Evidence is mounting that Convolutional Networks (ConvNets) are the most effective representation learning method for visual recognition tasks. In the common scenario, a ConvNet is…
Self-tuned Visual Subclass Learning with Shared Samples An Incremental Approach
Hossein Azizpour, Stefan Carlsson
Computer vision tasks are traditionally defined and evaluated using semantic categories. However, it is known to the field that semantic classes do not necessarily correspond to a…
CNN Features off-the-shelf: an Astounding Baseline for Recognition
Ali Sharif Razavian, Hossein Azizpour, Josephine Sullivan +1
Recent results indicate that the generic descriptors extracted from the convolutional neural networks are very powerful. This paper adds to the mounting evidence that this is indee…