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MULTICULTURALISME DENSE OU VIOLENCE MASSIVE: QUATRE SCÉNARIOS POSSIBLES
Relief: Revue Électronique de Littérature Francaise, 2011 Devant leur pluralisation ethnoculturelle augmentant chaque jour davantage, les États peuvent recourir à quatre principaux modes d’action: l’asssimilation qui est une forme d’exclusion dans ses formes les plus violentes (monoculturalisme); la ...
Afef Benessaieh
doaj +8 more sources
Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions [PDF]
IEEE International Conference on Computer Vision, 2021 Although convolutional neural networks (CNNs) have achieved great success in computer vision, this work investigates a simpler, convolution-free backbone network use-fid for many dense prediction tasks.
Wenhai Wang +8 more
semanticscholar +1 more source
Dense Passage Retrieval for Open-Domain Question Answering [PDF]
Conference on Empirical Methods in Natural Language Processing, 2020 Open-domain question answering relies on efficient passage retrieval to select candidate contexts, where traditional sparse vector space models, such as TF-IDF or BM25, are the de facto method.
Vladimir Karpukhin +7 more
semanticscholar +1 more source
Vision Transformers for Dense Prediction [PDF]
IEEE International Conference on Computer Vision, 2021 We introduce dense prediction transformers, an architecture that leverages vision transformers in place of convolutional networks as a backbone for dense prediction tasks.
René Ranftl +2 more
semanticscholar +1 more source
Long-term Forecasting with TiDE: Time-series Dense Encoder [PDF]
Trans. Mach. Learn. Res., 2023 Recent work has shown that simple linear models can outperform several Transformer based approaches in long term time-series forecasting. Motivated by this, we propose a Multi-layer Perceptron (MLP) based encoder-decoder model, Time-series Dense Encoder (
Abhimanyu Das +5 more
semanticscholar +1 more source
Focal Loss for Dense Object Detection [PDF]
IEEE International Conference on Computer Vision, 2017 The highest accuracy object detectors to date are based on a two-stage approach popularized by R-CNN, where a classifier is applied to a sparse set of candidate object locations.
Tsung-Yi Lin +4 more
semanticscholar +2 more sources
RoMa: Robust Dense Feature Matching [PDF]
Computer Vision and Pattern Recognition, 2023 Feature matching is an important computer vision task that involves estimating correspondences between two images of a 3D scene, and dense methods estimate all such correspondences.
Johan Edstedt +4 more
semanticscholar +1 more source
Point-SLAM: Dense Neural Point Cloud-based SLAM [PDF]
IEEE International Conference on Computer Vision, 2023 We propose a dense neural simultaneous localization and mapping (SLAM) approach for monocular RGBD input which anchors the features of a neural scene representation in a point cloud that is iteratively generated in an input-dependent data-driven manner ...
Erik Sandström +3 more
semanticscholar +1 more source
Dense Distinct Query for End-to-End Object Detection [PDF]
Computer Vision and Pattern Recognition, 2023 One-to-one label assignment in object detection has successfully obviated the need for non-maximum suppression (NMS) as postprocessing and makes the pipeline end-to-end.
Shilong Zhang +7 more
semanticscholar +1 more source
Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense Video Captioning [PDF]
Computer Vision and Pattern Recognition, 2023 In this work, we introduce Vid2Seq, a multi-modal single-stage dense event captioning model pretrained on narrated videos which are readily-available at scale.
Antoine Yang +7 more
semanticscholar +1 more source