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08/31/2023
Dual-Decoder Consistency via Pseudo-Labels Guided Data Augmentation for Semi-Supervised Medical Image Segmentation
Medical image segmentation methods often rely on fully supervised approa...
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05/17/2023
Exploring Inductive Biases in Contrastive Learning: A Clustering Perspective
This paper investigates the differences in data organization between con...
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03/16/2023
A New Benchmark: On the Utility of Synthetic Data with Blender for Bare Supervised Learning and Downstream Domain Adaptation
Deep learning in computer vision has achieved great success with the pri...
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03/14/2023
Sr-init: An interpretable layer pruning method
Despite the popularization of deep neural networks (DNNs) in many fields...
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02/23/2023
Unsupervised Domain Adaptation via Distilled Discriminative Clustering
Unsupervised domain adaptation addresses the problem of classifying data...
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03/10/2022
Transferring Dual Stochastic Graph Convolutional Network for Facial Micro-expression Recognition
Micro-expression recognition has drawn increasing attention due to its w...
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10/28/2021
MEGAN: Memory Enhanced Graph Attention Network for Space-Time Video Super-Resolution
Space-time video super-resolution (STVSR) aims to construct a high space...
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08/20/2021
Geometry-Aware Self-Training for Unsupervised Domain Adaptationon Object Point Clouds
The point cloud representation of an object can have a large geometric v...
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06/14/2021
Object-Guided Instance Segmentation With Auxiliary Feature Refinement for Biological Images
Instance segmentation is of great importance for many biological applica...
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04/10/2021
On Universal Black-Box Domain Adaptation
In this paper, we study an arguably least restrictive setting of domain ...
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03/05/2021
Vicinal and categorical domain adaptation
Unsupervised domain adaptation aims to learn a task classifier that perf...
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12/08/2020
Towards Uncovering the Intrinsic Data Structures for Unsupervised Domain Adaptation using Structurally Regularized Deep Clustering
Unsupervised domain adaptation (UDA) is to learn classification models t...
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05/28/2020
Bipartite Distance for Shape-Aware Landmark Detection in Spinal X-Ray Images
Scoliosis is a congenital disease that causes lateral curvature in the s...
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05/05/2020
Partly Supervised Multitask Learning
Semi-supervised learning has recently been attracting attention as an al...
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04/15/2020
Analysis of Scoliosis From Spinal X-Ray Images
Scoliosis is a congenital disease in which the spine is deformed from it...
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03/19/2020
Unsupervised Domain Adaptation via Structurally Regularized Deep Clustering
Unsupervised domain adaptation (UDA) is to make predictions for unlabele...
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02/20/2020
Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice
In this paper, we study the formalism of unsupervised multi-class domain...
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12/09/2019
Shape-Aware Organ Segmentation by Predicting Signed Distance Maps
In this work, we propose to resolve the issue existing in current deep l...
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11/27/2019
Discriminative Adversarial Domain Adaptation
Given labeled instances on a source domain and unlabeled ones on a targe...
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11/20/2019
Object-Guided Instance Segmentation for Biological Images
Instance segmentation of biological images is essential for studying obj...
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04/09/2019
Domain-Symmetric Networks for Adversarial Domain Adaptation
Unsupervised domain adaptation aims to learn a model of classifier for u...
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11/25/2018
Generating Realistic Training Images Based on Tonality-Alignment Generative Adversarial Networks for Hand Pose Estimation
Hand pose estimation from a monocular RGB image is an important but chal...
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08/31/2018
3D Segmentation with Exponential Logarithmic Loss for Highly Unbalanced Object Sizes
With the introduction of fully convolutional neural networks, deep learn...
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08/15/2018
AnatomyNet: Deep 3D Squeeze-and-excitation U-Nets for fast and fully automated whole-volume anatomical segmentation
Radiation therapy (RT) is a common treatment for head and neck (HaN) can...
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07/28/2018
