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Found 6 papers, 0 papers with code
Boosting Few-Shot Learning via Attentive Feature Regularization
Few-shot learning (FSL) based on manifold regularization aims to improve the recognition capacity of novel objects with limited training samples by mixing two samples from different categories with a blending factor.
Towards Function Space Mesh Watermarking: Protecting the Copyright of Signed Distance Fields
Our method can recover the message with high-resolution meshes extracted from SDFs and detect the watermark even when mesh vertices are extremely sparse.
Clothes Grasping and Unfolding Based on RGB-D Semantic Segmentation
These methods often utilize physics engines to synthesize depth images to reduce the cost of real labeled data collection.
Understanding Edge-of-Stability Training Dynamics with a Minimalist Example
Globally we observe that the training dynamics for our example has an interesting bifurcating behavior, which was also observed in the training of neural nets.
YNU-HPCC at SemEval-2021 Task 6: Combining ALBERT and Text-CNN for Persuasion Detection in Texts and Images
In recent years, memes combining image and text have been widely used in social media, and memes are one of the most popular types of content used in online disinformation campaigns.
Dissecting Hessian: Understanding Common Structure of Hessian in Neural Networks
We can analyze the properties of these smaller matrices and prove the structure of top eigenspace random 2-layer networks.
