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08/23/2023
Rethinking Data Perturbation and Model Stabilization for Semi-supervised Medical Image Segmentation
Studies on semi-supervised medical image segmentation (SSMIS) have seen ...
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05/11/2023
EfficientViT: Memory Efficient Vision Transformer with Cascaded Group Attention
Vision transformers have shown great success due to their high model cap...
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01/22/2023
Bidirectional Propagation for Cross-Modal 3D Object Detection
Recent works have revealed the superiority of feature-level fusion for c...
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01/02/2023
CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection
An increasing number of public datasets have shown a marked clinical imp...
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12/20/2022
A Comprehensive Study and Comparison of the Robustness of 3D Object Detectors Against Adversarial Attacks
Deep learning-based 3D object detectors have made significant progress i...
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09/26/2022
A heterogeneous group CNN for image super-resolution
Convolutional neural networks (CNNs) have obtained remarkable performanc...
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07/06/2022
GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation
The inherent ambiguity in ground-truth annotations of 3D bounding boxes ...
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06/16/2022
Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy Labels
Noisy labels collected with limited annotation cost prevent medical imag...
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05/29/2022
Image Super-resolution with An Enhanced Group Convolutional Neural Network
CNNs with strong learning abilities are widely chosen to resolve super-r...
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04/06/2022
Towards Robust Adaptive Object Detection under Noisy Annotations
Domain Adaptive Object Detection (DAOD) models a joint distribution of i...
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03/22/2022
IDEA-Net: Dynamic 3D Point Cloud Interpolation via Deep Embedding Alignment
This paper investigates the problem of temporally interpolating dynamic ...
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03/12/2022
SIGMA: Semantic-complete Graph Matching for Domain Adaptive Object Detection
Domain Adaptive Object Detection (DAOD) leverages a labeled domain to le...
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10/24/2021
Exploring Gradient Flow Based Saliency for DNN Model Compression
Model pruning aims to reduce the deep neural network (DNN) model size or...
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10/01/2021
Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning
Nowadays, deep learning methods with large-scale datasets can produce cl...
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07/07/2021
Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification
The amount of medical images for training deep classification models is ...
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03/09/2021
MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic Segmentation
Unsupervised domain adaptation (UDA) aims to transfer the knowledge from...
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01/12/2020
Complementary Network with Adaptive Receptive Fields for Melanoma Segmentation
Automatic melanoma segmentation in dermoscopic images is essential in co...
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12/16/2019
