mlsanityData to 14 Oct 2026

Multi-temporal Calving Front Segmentation

arXiv 2512.11560 ↗First posted 12 Dec 2025cs.CV cs.AIcited by 2

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Abstract (arXiv)

The calving fronts of marine-terminating glaciers undergo constant changes. These changes significantly affect the glacier's mass and dynamics, demanding continuous monitoring. To address this need, deep learning models were developed that can automatically delineate the calving front in Synthetic Aperture Radar imagery. However, these models often struggle to correctly classify areas affected by seasonal conditions such as ice melange or snow-covered surfaces. To address this issue, we propose to process multiple frames from a satellite image time series of the same glacier in parallel and exchange temporal information between the corresponding feature maps to stabilize each prediction. We integrate our approach into the current state-of-the-art architecture Tyrion and accomplish a new state-of-the-art performance on the CaFFe benchmark dataset. In particular, we achieve a Mean Distance Error of 184.4 m and a mean Intersection over Union of 83.6.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 39 of its 85 references that are in the map. First posted on arXiv 12 Dec 2025.

Builds on

39 of 85 references.

References · 39

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  4. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  5. 2017mixup: Beyond Empirical Risk Minimizationcited by 5,183
  6. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,057
  7. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,253
  8. 2021SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformerscited by 2,940
  9. 2019CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Featurescited by 2,884
  10. 2017Rethinking Atrous Convolution for Semantic Image Segmentationcited by 2,161
  11. 2018Group Normalizationcited by 1,524
  12. 2015Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcastingcited by 1,436
27 more
  1. 2017Random Erasing Data Augmentationcited by 1,239
  2. 2021Swin Transformer V2: Scaling Up Capacity and Resolutioncited by 1,228
  3. 2017A Closer Look at Spatiotemporal Convolutions for Action Recognitioncited by 1,143
  4. 2021Segmenter: Transformer for Semantic Segmentationcited by 855
  5. 2020ReZero is All You Need: Fast Convergence at Large Depthcited by 264
  6. 2015Delving Deeper into Convolutional Networks for Learning Video Representationscited by 148
  7. 2021Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networkscited by 143
  8. 2021Semi-supervised Semantic Segmentation with Directional Context-aware Consistencycited by 112
  9. 2022Changer: Feature Interaction is What You Need for Change Detectioncited by 79
  10. 2019Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attentioncited by 71
  11. 2018Multi-Temporal Land Cover Classification with Sequential Recurrent Encoderscited by 61
  12. 2020Lightweight Temporal Self-Attention for Classifying Satellite Image Time Seriescited by 55
  13. 2021SeMask: Semantically Masked Transformers for Semantic Segmentationcited by 55
  14. 2022Joint Spatio-Temporal Modeling for the Semantic Change Detection in Remote Sensing Imagescited by 43
  15. 2019Detecting Urban Changes with Recurrent Neural Networks from Multitemporal Sentinel-2 Datacited by 20
  16. 2021HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastlinecited by 13
  17. 2023MapFormer: Boosting Change Detection by Using Pre-change Informationcited by 12
  18. 2021Glacier Calving Front Segmentation Using Attention U-Netcited by 10
  19. 2022Inferring 3D change detection from bitemporal optical imagescited by 10
  20. 2021Bayesian U-Net for Segmenting Glaciers in SAR Imagerycited by 8
  21. 2023AMD-HookNet for Glacier Front Segmentationcited by 7
  22. 2024Satellite Image Time Series Semantic Change Detection: Novel Architecture and Analysis of Domain Shiftcited by 6
  23. 2021On Mathews Correlation Coefficient and Improved Distance Map Loss for Automatic Glacier Calving Front Segmentation in SAR Imagerycited by 5
  24. 2021Pixel-wise Distance Regression for Glacier Calving Front Detection and Segmentationcited by 5
  25. 2024Continuous Urban Change Detection from Satellite Image Time Series with Temporal Feature Refinement and Multi-Task Integrationcited by 5
  26. 2023Unsupervised CD in satellite image time series by contrastive learning and feature trackingcited by 3
  27. 2025SSL4SAR: Self-Supervised Learning for Glacier Calving Front Extraction from SAR Imagerycited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Few-Shot Domain Adaptation with Temporal References and Static Priors for Glacier Calving Front Delineationcited by 0
  2. 2026Evaluating Zone-Guided Front Extraction for Glacier Calving-Front Delineation in SAR Imagerycited by 0