Deep Multimodal Fusion for Semantic Segmentation of Remote Sensing Earth
Observation Data

Deep Multimodal Fusion for Semantic Segmentation of Remote Sensing Earth Observation Data

1 October 2024

Vlatko Spasev

Ivan Kitanovski

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Papers citing "Deep Multimodal Fusion for Semantic Segmentation of Remote Sensing Earth Observation Data"

7 / 7 papers shown

Title
FLAIR: a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical Imagery A. Garioud Nicolas Gonthier Loic Landrieu Apolline De Wit Marion Valette Marc Poupée S. Giordano Boris Wattrelos 72 23 0 20 Oct 2023
MaxViT: Multi-Axis Vision Transformer Zhengzhong Tu Hossein Talebi Han Zhang Feng Yang P. Milanfar A. Bovik Yinxiao Li ViT 131 666 0 04 Apr 2022
UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery Libo Wang Rui Li Ce Zhang Shenghui Fang Chenxi Duan Xiaoliang Meng P. M. Atkinson ViT 69 665 0 18 Sep 2021
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks Vivien Sainte Fare Garnot Loic Landrieu AI4TS 134 162 0 16 Jul 2021
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers Sixiao Zheng Jiachen Lu Hengshuang Zhao Xiatian Zhu Zekun Luo ... Yanwei Fu Jianfeng Feng Tao Xiang Philip Torr Li Zhang ViT 194 2,911 0 31 Dec 2020
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation Liang-Chieh Chen Yukun Zhu George Papandreou Florian Schroff Hartwig Adam SSeg 480 13,178 0 07 Feb 2018
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs Liang-Chieh Chen George Papandreou Iasonas Kokkinos Kevin Patrick Murphy Alan Yuille SSeg 267 18,267 0 02 Jun 2016