Search Results for author:
Found 4 papers, 3 papers with code
Back to 3D: Few-Shot 3D Keypoint Detection with Back-Projected 2D Features
In this work, we propose to explore foundation models for the task of keypoint detection on 3D shapes.
Language Models for German Text Simplification: Overcoming Parallel Data Scarcity through Style-specific Pre-training
Moreover, with the style-specific pre-training, we reduced the number of trainable parameters in text simplification models.
Joint MR sequence optimization beats pure neural network approaches for spin-echo MRI super-resolution
The found radiofrequency pulse train designs generate an optimal signal for the NN to perform the SR task.
Scale-Equivariant Deep Learning for 3D Data
The ability of convolutional neural networks (CNNs) to recognize objects regardless of their position in the image is due to the translation-equivariance of the convolutional operation.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
