Results 31 to 40 of about 4,996,743 (329)
Unsupervised Visual Representation Learning by Synchronous Momentum Grouping [PDF]
European Conference on Computer Vision, 2022 In this paper, we propose a genuine group-level contrastive visual representation learning method whose linear evaluation performance on ImageNet surpasses the vanilla supervised learning.
Bo Pang +4 more
semanticscholar +1 more source
Enhance the Visual Representation via Discrete Adversarial Training [PDF]
Neural Information Processing Systems, 2022 Adversarial Training (AT), which is commonly accepted as one of the most effective approaches defending against adversarial examples, can largely harm the standard performance, thus has limited usefulness on industrial-scale production and applications ...
Xiaofeng Mao +8 more
semanticscholar +1 more source
Mutual Contrastive Learning for Visual Representation Learning [PDF]
AAAI Conference on Artificial Intelligence, 2021 We present a collaborative learning method called Mutual Contrastive Learning (MCL) for general visual representation learning. The core idea of MCL is to perform mutual interaction and transfer of contrastive distributions among a cohort of networks.
Chuanguang Yang +3 more
semanticscholar +1 more source
Unsupervised Visual Representation Learning by Context Prediction [PDF]
IEEE International Conference on Computer Vision, 2015 This work explores the use of spatial context as a source of free and plentiful supervisory signal for training a rich visual representation. Given only a large, unlabeled image collection, we extract random pairs of patches from each image and train a ...
Carl Doersch, A. Gupta, Alexei A. Efros
semanticscholar +1 more source
Multimodal Contrastive Training for Visual Representation Learning [PDF]
Computer Vision and Pattern Recognition, 2021 We develop an approach to learning visual representations that embraces multimodal data, driven by a combination of intra- and inter-modal similarity preservation objectives.
Xin Yuan +7 more
semanticscholar +1 more source
OpenMixup: Open Mixup Toolbox and Benchmark for Visual Representation Learning [PDF]
arXiv.org, 2022 Mixup augmentation has emerged as a widely used technique for improving the generalization ability of deep neural networks (DNNs). However, the lack of standardized implementations and benchmarks has impeded recent progress, resulting in poor ...
Siyuan Li +4 more
semanticscholar +1 more source
When Does Contrastive Visual Representation Learning Work? [PDF]
Computer Vision and Pattern Recognition, 2021 Recent self-supervised representation learning techniques have largely closed the gap between supervised and unsupervised learning on ImageNet classification.
Elijah Cole +4 more
semanticscholar +1 more source
Future Internet, 2014 Digesting the data hose that cities are constantly producing is complex; data is usually structured with different criteria, which makes comparative analysis of multiple cities challenging.
Francesc Valls Dalmau +3 more
doaj +1 more source
Contemporary Southeastern Europe, 2020 The Balkans and South Caucasia (Eurasia Minor) consists of countries and regions that are considered by representative investigations on the country level as some of the last strongholds of patriarchy compared to the rest of Europe, Russia not included.
Karl Kaser
doaj +1 more source
Creativity Studies, 2011 This paper represents an examination of recent research in the fields of urban planning, visual artwork, visual image and text analysis, according to which the increasing importance of visual representation in modern society has altered the traditional ...
Ilze Paklone
doaj +1 more source