47 citations · 81 across the 5 of their papers we have counts for
7 papers
MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction
Yuanhao Cai, Jing Lin, Zudi Lin +5
Existing leading methods for spectral reconstruction (SR) focus on designing deeper or wider convolutional neural networks (CNNs) to learn the end-to-end mapping from the RGB image…
Instance Segmentation of Unlabeled Modalities via Cyclic Segmentation GAN
Leander Lauenburg, Zudi Lin, Ruihan Zhang +6
Instance segmentation for unlabeled imaging modalities is a challenging but essential task as collecting expert annotation can be expensive and time-consuming. Existing works segme…
Revisiting RCAN: Improved Training for Image Super-Resolution
Zudi Lin, Prateek Garg, Atmadeep Banerjee +6
Image super-resolution (SR) is a fast-moving field with novel architectures attracting the spotlight. However, most SR models were optimized with dated training strategies. In this…
Asymmetric 3D Context Fusion for Universal Lesion Detection
Jiancheng Yang, Yi He, Kaiming Kuang +3
Modeling 3D context is essential for high-performance 3D medical image analysis. Although 2D networks benefit from large-scale 2D supervised pretraining, it is weak in capturing 3D…
AxonEM Dataset: 3D Axon Instance Segmentation of Brain Cortical Regions
Donglai Wei, Kisuk Lee, Hanyu Li +13
Electron microscopy (EM) enables the reconstruction of neural circuits at the level of individual synapses, which has been transformative for scientific discoveries. However, due t…
White-Box Adversarial Defense via Self-Supervised Data Estimation
Zudi Lin, Hanspeter Pfister, Ziming Zhang
In this paper, we study the problem of how to defend classifiers against adversarial attacks that fool the classifiers using subtly modified input data. In contrast to previous wor…