IEEE

PE-Attack: On the Universal Positional Embedding Vulnerability in Transformer-Based Models

Abstract: The Transformer model has gained significant recognition for its remarkable computational capabilities and versatility, positioning itself as a fundamental component in numerous practical ...
IEEE

Graph transformer with structural embedding and training for hyperspectral image

Abstract: Graph transformer networks have received more attention in hyperspectral image (HSI) classification. However, they overlooked the influence of graph connectivity strength in positional ...
GitHub

DVEFormer: Efficient Prediction of Dense Visual Embeddings via Distillation and RGB-D Transformers

This repository contains the code to our paper "Efficient Prediction of Dense Visual Embeddings via Distillation and RGB-D Transformers" (Accepted at IROS 2025) The repository includes code for ...