LAUSR

Instance-Level Embedding Adaptation for Few-Shot Learning

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0 Published in 2019 at "IEEE Access"

DOI: 10.1109/access.2019.2906665

Abstract: Few-shot learning aims to recognize novel categories from just a few labeled instances. Existing metric learning-based approaches perform classifications by nearest neighbor search in the embedding space. The embedding function is a deep neural network… read more here.

Keywords: adaptation; instance level; shot learning; instance ... See more keywords

Volumetric Instance-Level Semantic Mapping Via Multi-View 2D-to-3D Label Diffusion

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1 Published in 2022 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2022.3146502

Abstract: Robots operating in real-world settings often need to plan interactions with surrounding scene elements and therefore, it is crucial for them to understand their workspace at the level of individual objects. In this spirit, this… read more here.

Keywords: instance level; level; multi view; instance ... See more keywords

i2c-net: Using Instance-Level Neural Networks for Monocular Category-Level 6D Pose Estimation

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2 Published in 2023 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2023.3240362

Abstract: Object detection and pose estimation are strict requirements for many robotic grasping and manipulation applications to endow robots with the ability to grasp objects with different properties in cluttered scenes and with various lighting conditions.… read more here.

Keywords: instance level; i2c net; pose estimation; level ... See more keywords

Soft Instance-Level Domain Adaptation With Virtual Classifier for Unsupervised Hyperspectral Image Classification

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2 Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2023.3266790

Abstract: Adversarial learning-based unsupervised hyperspectral image (HSI) classification methods usually adapt probability distributions by minimizing the statistical distance between similar pixels of different HSIs. Since adversarial learning may weaken the discriminability of features, the extracted features… read more here.

Keywords: instance level; domain; virtual classifier;

RelightGAN: Instance-level Generative Adversarial Network for Face Illumination Transfer

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0 Published in 2021 at "IEEE Transactions on Image Processing"

DOI: 10.1109/tip.2021.3061933

Abstract: Face illumination perception and processing is a significantly difficult issue especially due to asymmetric shadings, local highlights, and local shadows. This study focuses on the face illumination transfer problem, which is to transfer the illumination… read more here.

Keywords: face; instance level; transfer; face illumination ... See more keywords

AIParsing: Anchor-Free Instance-Level Human Parsing

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1 Published in 2022 at "IEEE Transactions on Image Processing"

DOI: 10.1109/tip.2022.3192989

Abstract: Most state-of-the-art instance-level human parsing models adopt two-stage anchor-based detectors and, therefore, cannot avoid the heuristic anchor box design and the lack of analysis on a pixel level. To address these two issues, we have… read more here.

Keywords: instance level; human parsing; anchor free; level ... See more keywords

LLP-GAN: A GAN-Based Algorithm for Learning From Label Proportions.

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1 Published in 2022 at "IEEE transactions on neural networks and learning systems"

DOI: 10.1109/tnnls.2022.3149926

Abstract: Learning from label proportions (LLP) is a widespread and important learning paradigm: only the bag-level proportional information of the grouped training instances is available for the classification task, instead of the instance-level labels in the… read more here.

Keywords: instance level; llp gan; learning label; label proportions ... See more keywords

Contextual Instance Decoupling for Instance-Level Human Analysis.

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2 Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"

DOI: 10.1109/tpami.2023.3243223

Abstract: One fundamental challenge of instance-level human analysis is to decouple instances in crowded scenes, where multiple persons are overlapped with each other. This paper proposes the Contextual Instance Decoupling (CID), which presents a new pipeline… read more here.

Keywords: instance level; person; segmentation; analysis ... See more keywords