Deep Learning for Satellite Imagery (IN2107)

Deep Learning for Satellite Imagery (IN2107)

Satellite imagery contains significant clues for observing and perceiving the earth’s surface on a global scale. In recent times, deep learning techniques play an important role for automatically analyzing such data. Relevant applications cover geo-localization, time-series satellite imagery understanding, classification, and segmentation. Research papers and methods devised for this kind of data are subject to unique challenges compared to standard computer vision tasks/benchmarks. In this seminar, we provide an overview of common deep learning techniques, datasets and central works that employ satellite imagery.

General information

Date: Thursdays (10:00-11:00)

Location: Virtual event. Zoom link and password will be shared via email.

Lecturers: Prof. Dr. Laura Leal-Taixé and Aysim Toker.


SWS: 2


Course matching

Students are supposed to register to the Matching-System between July 22nd and 27th. See the Matching-System FAQ for more details.

After the final matching is announced on August 5th, we will send an email with further information.


  1. Where Am I Looking At? Joint Location and Orientation Estimation by Cross-View Matching. Shi, Yujiao, et al. (CVPR 2020).
  2. VIGOR: Cross-View Image Geo-Localization Beyond One-to-One Retrieval. Zhu, Sijie, et al. (CVPR 2021).
  3. TransGeo: Transformer Is All You Need for Cross-View Image Geo-Localization. Zhu, Sijie, et al. (CVPR 2022).
  4. Cross-view Geo-localization with Layer-to-Layer Transformer. Yang, Hongji, et al. (NeurIPS 2021).
  5. Video Geo-Localization Employing Geo-Temporal Feature Learning and GPS Trajectory Smoothing. Regmi, Krishna, et al. (ICCV 2021).
  6. Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery. Zheng, Zhuo, et al. (CVPR 2020).
  7. PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation. Li, Xiangtai, et al. (CVPR 2021).
  8. Sparse and Complete Latent Organization for Geospatial Semantic Segmentation. Yang, Fengyu, and Chenyang Ma. (CVPR 2022).
  9. Revisiting Near/Remote Sensing with Geospatial Attention. Workman, Scott, et al. (CVPR 2022).
  10. Geometry-Aware Satellite-to-Ground Image Synthesis for Urban Areas. Lu, Xiaohu, et al. (CVPR 2020).
  11. Cross-View Image Synthesis using Conditional GANs. Regmi, Krishna, and Ali Borji. (CVPR 2018).
  12. The Multi-Temporal Urban Development SpaceNet Dataset. Van Etten, Adam, et al. (CVPR 2021).
  13. Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks. Garnot, Vivien Sainte Fare, and Loic Landrieu. (ICCV 2021).

After being matched to the seminar, please send a list of your 3 favourite papers to Topics are assigned on a first-come-first-serve basis.