416 citations · 1.8k across the 68 of their papers we have counts for
20 papers · 1 filter
Context-LGM: Leveraging Object-Context Relation for Context-Aware Object Recognition
Mingzhou Liu, Xinwei Sun, Fandong Zhang +2
Context, as referred to situational factors related to the object of interest, can help infer the object's states or properties in visual recognition. As such contextual features a…
Preservational Learning Improves Self-supervised Medical Image Models by Reconstructing Diverse Contexts
Hong-Yu Zhou, Chixiang Lu, Sibei Yang +2
Preserving maximal information is one of principles of designing self-supervised learning methodologies. To reach this goal, contrastive learning adopts an implicit way which is co…
nnFormer: Interleaved Transformer for Volumetric Segmentation
Hong-Yu Zhou, Jiansen Guo, Yinghao Zhang +3
Transformer, the model of choice for natural language processing, has drawn scant attention from the medical imaging community. Given the ability to exploit long-term dependencies,…
Multi-scale Matching Networks for Semantic Correspondence
Dongyang Zhao, Ziyang Song, Zhenghao Ji +3
Deep features have been proven powerful in building accurate dense semantic correspondences in various previous works. However, the multi-scale and pyramidal hierarchy of convoluti…
CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation
Xinru Zhang, Chenghao Liu, Ni Ou +5
Brain lesion segmentation provides a valuable tool for clinical diagnosis, and convolutional neural networks (CNNs) have achieved unprecedented success in the task. Data augmentati…
ConvNets vs. Transformers: Whose Visual Representations are More Transferable?
Hong-Yu Zhou, Chixiang Lu, Sibei Yang +1
Vision transformers have attracted much attention from computer vision researchers as they are not restricted to the spatial inductive bias of ConvNets. However, although Transform…