Paper accepted at International Conference on Multimedia Information Processing and Retrieval (MIPR) 2024_伟德国际_伟德国际1946$娱乐app游戏

Chair for Machine Learning & Computer Vision
2024-05-24T07:49:00.271605+00:00
Universit?t Augsburg

The paper titled "Segformer++: Efficient Token-Merging Strategies for High-Resolution Semantic Segmentation" by Daniel Kienzle, Marco Kantonis, Robin Sch?n, and Rainer Lienhart has been accepted at the IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR) 2024. The paper describes a new method to enhance the efficiency of transformer models. This enables the application of computationally intensive transformer models to high-resolution images. Further information about this paper can be found at https://kiedani.github.io/MIPR2024/.