We propose a novel transformer-based framework that reconstructs two hig...
In this paper, we study Text-to-3D content generation leveraging 2D diff...
Steerable models can provide very general and flexible equivariance by
f...
This work investigates the use of robust optimal transport (OT) for shap...
Contrastive learning applied to self-supervised representation learning ...
Spherical signals exist in many applications, e.g., planetary data, LiDA...
Registration of images with pathologies is challenging due to tissue
app...
Recent research has shown that incorporating equivariance into neural ne...
We introduce a fluid-based image augmentation method for medical image
a...
We introduce a region-specific diffeomorphic metric mapping (RDMM)
regis...
We introduce an end-to-end deep-learning framework for 3D medical image
...
This paper proposes a multi-level feature learning framework for human a...
In this paper, we propose an innovative end-to-end subtitle detection an...