Results 21 to 30 of about 1,634,168 (383)
SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 Domain adaptive semantic segmentation attempts to make satisfactory dense predictions on an unlabeled target domain by utilizing the supervised model trained on a labeled source domain. One popular solution is self-training, which retrains the model with
Binhui Xie +5 more
semanticscholar +1 more source
Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning [PDF]
Computer Vision and Pattern Recognition, 2020 Contrastive learning methods for unsupervised visual representation learning have reached remarkable levels of transfer performance. We argue that the power of contrastive learning has yet to be fully unleashed, as current methods are trained only on ...
Zhenda Xie +5 more
semanticscholar +1 more source
Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentation [PDF]
Computer Vision and Pattern Recognition, 2021 Existing studies in weakly-supervised semantic segmentation (WSSS) using image-level weak supervision have several limitations: sparse object coverage, inaccurate object boundaries, and co-occurring pixels from non-target objects.
Seungho Lee +3 more
semanticscholar +1 more source
Efficient Image Super-Resolution Using Pixel Attention [PDF]
ECCV Workshops, 2020 This work aims at designing a lightweight convolutional neural network for image super resolution (SR). With simplicity bare in mind, we construct a pretty concise and effective network with a newly proposed pixel attention scheme.
Hengyuan Zhao +4 more
semanticscholar +1 more source
PVNet: Pixel-Wise Voting Network for 6DoF Pose Estimation [PDF]
Computer Vision and Pattern Recognition, 2018 This paper addresses the challenge of 6DoF pose estimation from a single RGB image under severe occlusion or truncation. Many recent works have shown that a two-stage approach, which first detects keypoints and then solves a Perspective-n-Point (PnP ...
Sida Peng +4 more
semanticscholar +1 more source
Weakly Supervised Learning of Instance Segmentation With Inter-Pixel Relations [PDF]
Computer Vision and Pattern Recognition, 2019 This paper presents a novel approach for learning instance segmentation with image-level class labels as supervision. Our approach generates pseudo instance segmentation labels of training images, which are used to train a fully supervised model.
Jiwoon Ahn, Sunghyun Cho, Suha Kwak
semanticscholar +1 more source
Single-pixel ptychography [PDF]
Optics Letters, 2021 Ptychography is a predominant non-interferometric technique to image large complex fields but with quite a narrow working spectrum, because diffraction measurements require dense array detection with an ultra-high dynamic range. Here we report a single-pixel ptychography technique that realizes non-interferometric and non-scanning complex-field imaging
Meng Li +8 more
openaire +2 more sources
RESEARCH AND PROTOTYPING METHODS OF STEGANOGRAPHY USING MOSAIC
Сучасні інформаційні системи, 2020 The paper considers the possibility of using a mosaic composed of many miniature images to hide the fact of text information transmission. The results of the study of optimal mosaic construction when using steganographic methods of hiding information are
Volodymyr Pevnev, Yurii Voikov
doaj +1 more source
Fully Depleted, Trench-Pinned Photo Gate for CMOS Image Sensor Applications
Sensors, 2020 Tackling issues of implantation-caused defects and contamination, this paper presents a new complementary metal−oxide−semiconductor (CMOS) image sensor (CIS) pixel design concept based on a native epitaxial layer for photon detection, charge ...
Francois Roy +10 more
doaj +1 more source
Pixel-Perfect Structure-from-Motion with Featuremetric Refinement [PDF]
IEEE International Conference on Computer Vision, 2021 Finding local features that are repeatable across multiple views is a cornerstone of sparse 3D reconstruction. The classical image matching paradigm detects keypoints per-image once and for all, which can yield poorly-localized features and propagate ...
Paul-Edouard Sarlin +3 more
semanticscholar +1 more source