research
∙
07/15/2023
Neural Deformable Models for 3D Bi-Ventricular Heart Shape Reconstruction and Modeling from 2D Sparse Cardiac Magnetic Resonance Imaging
We propose a novel neural deformable model (NDM) targeting at the recons...
share
research
∙
06/09/2023
On the Challenges and Perspectives of Foundation Models for Medical Image Analysis
This article discusses the opportunities, applications and future direct...
research
∙
06/08/2023
Improving Negative-Prompt Inversion via Proximal Guidance
DDIM inversion has revealed the remarkable potential of real image editi...
research
∙
04/27/2023
Learning Articulated Shape with Keypoint Pseudo-labels from Web Images
This paper shows that it is possible to learn models for monocular 3D re...
research
∙
04/02/2023
Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies
Transformations based on domain expertise (expert transformations), such...
research
∙
03/20/2023
SVDiff: Compact Parameter Space for Diffusion Fine-Tuning
Diffusion models have achieved remarkable success in text-to-image gener...
research
∙
12/08/2022
SINE: SINgle Image Editing with Text-to-Image Diffusion Models
Recent works on diffusion models have demonstrated a strong capability f...
research
∙
12/08/2022
Diffusion Guided Domain Adaptation of Image Generators
Can a text-to-image diffusion model be used as a training objective for ...
research
∙
09/16/2022
Automatic Tooth Segmentation from 3D Dental Model using Deep Learning: A Quantitative Analysis of what can be learnt from a Single 3D Dental Model
3D tooth segmentation is an important task for digital orthodontics. Sev...
research
∙
06/18/2022
A Dynamic Data Driven Approach for Explainable Scene Understanding
Scene-understanding is an important topic in the area of Computer Vision...
research
∙
03/24/2022
A Manifold View of Adversarial Risk
The adversarial risk of a machine learning model has been widely studied...
research
∙
03/21/2022
Global Matching with Overlapping Attention for Optical Flow Estimation
Optical flow estimation is a fundamental task in computer vision. Recent...
research
∙
03/21/2022
TransFusion: Multi-view Divergent Fusion for Medical Image Segmentation with Transformers
Combining information from multi-view images is crucial to improve the p...
research
∙
03/04/2022
Show Me What and Tell Me How: Video Synthesis via Multimodal Conditioning
Most methods for conditional video synthesis use a single modality as th...
research
∙
02/28/2022
A Multi-scale Transformer for Medical Image Segmentation: Architectures, Model Efficiency, and Benchmarks
Transformers have emerged to be successful in a number of natural langua...
research
∙
01/22/2022
Modality Bank: Learn multi-modality images across data centers without sharing medical data
Multi-modality images have been widely used and provide comprehensive in...
research
∙
01/21/2022
Contrastive and Selective Hidden Embeddings for Medical Image Segmentation
Medical image segmentation has been widely recognized as a pivot procedu...
research
∙
01/19/2022
ASL Video Corpora Sign Bank: Resources Available through the American Sign Language Linguistic Research Project (ASLLRP)
The American Sign Language Linguistic Research Project (ASLLRP) provides...
research
∙
10/17/2021
AE-StyleGAN: Improved Training of Style-Based Auto-Encoders
StyleGANs have shown impressive results on data generation and manipulat...
research
∙
09/29/2021
Semi-Supervised Segmentation of Radiation-Induced Pulmonary Fibrosis from Lung CT Scans with Multi-Scale Guided Dense Attention
Computed Tomography (CT) plays an important role in monitoring radiation...
research
∙
09/10/2021
Global and Local Interpretation of black-box Machine Learning models to determine prognostic factors from early COVID-19 data
The COVID-19 corona virus has claimed 4.1 million lives, as of July 24, ...
research
∙
08/20/2021
Dual Projection Generative Adversarial Networks for Conditional Image Generation
Conditional Generative Adversarial Networks (cGANs) extend the standard ...
research
∙
07/02/2021
UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation
Transformer architecture has emerged to be successful in a number of nat...
research
∙
03/30/2021
Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training
Data augmentation has proved extremely useful by increasing training dat...
research
∙
03/05/2021
Liver Fibrosis and NAS scoring from CT images using self-supervised learning and texture encoding
Non-alcoholic fatty liver disease (NAFLD) is one of the most common caus...
research
∙
03/04/2021
DeepTag: An Unsupervised Deep Learning Method for Motion Tracking on Cardiac Tagging Magnetic Resonance Images
Cardiac tagging magnetic resonance imaging (t-MRI) is the gold standard ...
research
∙
02/09/2021
Training Federated GANs with Theoretical Guarantees: A Universal Aggregation Approach
Recently, Generative Adversarial Networks (GANs) have demonstrated their...
research
∙
02/04/2021
SelfNorm and CrossNorm for Out-of-Distribution Robustness
Normalization techniques are crucial in stabilizing and accelerating the...
research
∙
12/09/2020
A Topological Filter for Learning with Label Noise
Noisy labels can impair the performance of deep neural networks. To tack...
research
∙
12/02/2020
Learning View-Disentangled Human Pose Representation by Contrastive Cross-View Mutual Information Maximization
We introduce a novel representation learning method to disentangle pose-...
research
∙
11/19/2020
Error-Bounded Correction of Noisy Labels
To collect large scale annotated data, it is inevitable to introduce lab...
research
∙
10/15/2020
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness
Adversarial data augmentation has shown promise for training robust deep...
research
∙
09/22/2020
Deep Learning based NAS Score and Fibrosis Stage Prediction from CT and Pathology Data
Non-Alcoholic Fatty Liver Disease (NAFLD) is becoming increasingly preva...
research
∙
08/25/2020
Measure Anatomical Thickness from Cardiac MRI with Deep Neural Networks
Accurate estimation of shape thickness from medical images is crucial in...
research
∙
08/19/2020
Enhanced MRI Reconstruction Network using Neural Architecture Search
The accurate reconstruction of under-sampled magnetic resonance imaging ...
research
∙
08/18/2020
PC-U Net: Learning to Jointly Reconstruct and Segment the Cardiac Walls in 3D from CT Data
The 3D volumetric shape of the heart's left ventricle (LV) myocardium (M...
research
∙
08/17/2020
Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors
Oriented object detection in aerial images is a challenging task as the ...
research
∙
07/17/2020
OnlineAugment: Online Data Augmentation with Less Domain Knowledge
Data augmentation is one of the most important tools in training modern ...
research
∙
07/17/2020
Learn distributed GAN with Temporary Discriminators
In this work, we propose a method for training distributed GAN with sequ...
research
∙
06/13/2020
Unbiased Auxiliary Classifier GANs with MINE
Auxiliary Classifier GANs (AC-GANs) are widely used conditional generati...
research
∙
03/15/2020
MotionNet: Joint Perception and Motion Prediction for Autonomous Driving Based on Bird's Eye View Maps
The ability to reliably perceive the environmental states, particularly ...
research
∙
11/25/2019
Point Cloud Processing via Recurrent Set Encoding
We present a new permutation-invariant network for 3D point cloud proces...
research
∙
11/21/2019
Robust Conditional GAN from Uncertainty-Aware Pairwise Comparisons
Conditional generative adversarial networks have shown exceptional gener...
research
∙
07/25/2019
Unsupervised Domain Adaptation via Calibrating Uncertainties
Unsupervised domain adaptation (UDA) aims at inferring class labels for ...
research
∙
02/22/2019
Effective 3D Humerus and Scapula Extraction using Low-contrast and High-shape-variability MR Data
For the initial shoulder preoperative diagnosis, it is essential to obta...
research
∙
10/18/2018
MRI Reconstruction via Cascaded Channel-wise Attention Network
We consider an MRI reconstruction problem with input of k-space data at ...
research
∙
08/07/2018
Quantized Densely Connected U-Nets for Efficient Landmark Localization
In this paper, we propose quantized densely connected U-Nets for efficie...
research
∙
07/26/2018
Learning to Forecast and Refine Residual Motion for Image-to-Video Generation
We consider the problem of image-to-video translation, where an input im...
research
∙
05/24/2018
Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation
Random data augmentation is a critical technique to avoid overfitting in...
research
∙
05/21/2018