mlsanityData to 14 Oct 2026

Aerial View River Landform Video segmentation: A Weakly Supervised Context-aware Temporal Consistency Distillation Approach

arXiv 2511.16343 ↗First posted 20 Nov 2025cs.CVcited by 0

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Abstract (arXiv)

The study of terrain and landform classification through UAV remote sensing diverges significantly from ground vehicle patrol tasks. Besides grappling with the complexity of data annotation and ensuring temporal consistency, it also confronts the scarcity of relevant data and the limitations imposed by the effective range of many technologies. This research substantiates that, in aerial positioning tasks, both the mean Intersection over Union (mIoU) and temporal consistency (TC) metrics are of paramount importance. It is demonstrated that fully labeled data is not the optimal choice, as selecting only key data lacks the enhancement in TC, leading to failures. Hence, a teacher-student architecture, coupled with key frame selection and key frame updating algorithms, is proposed. This framework successfully performs weakly supervised learning and TC knowledge distillation, overcoming the deficiencies of traditional TC training in aerial tasks. The experimental results reveal that our method utilizing merely 30% of labeled data, concurrently elevates mIoU and temporal consistency ensuring stable localization of terrain objects. Result demo : https://gitlab.com/prophet.ai.inc/drone-based-riverbed-inspection

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 8 of its 20 references that are in the map. First posted on arXiv 20 Nov 2025.

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8 of 20 references.

References · 8

  1. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,223
  2. 2021Adaptive Prototype Learning and Allocation for Few-Shot Segmentationcited by 207
  3. 2019iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Imagescited by 197
  4. 2020Efficient Semantic Video Segmentation with Per-frame Inferencecited by 63
  5. 2022Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentationcited by 35
  6. 2021Video Salient Object Detection via Contrastive Features and Attention Modulescited by 13
  7. 2023Two-shot Video Object Segmentationcited by 7
  8. 2022Temporal Transductive Inference for Few-Shot Video Object Segmentationcited by 6

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  1. 2025High Temporal Consistency through Semantic Similarity Propagation in Semi-Supervised Video Semantic Segmentation for Autonomous Flight
  2. 2026DisDop: Distillation with Domain Priors for Open-Vocabulary Aerial Object Detection
  3. 2024Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imagery
  4. 2025Building Lightweight Semantic Segmentation Models for Aerial Images Using Dual Relation Distillation
  5. 2021A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial Images
  6. 2024Centerness-based Instance-aware Knowledge Distillation with Task-wise Mutual Lifting for Object Detection on Drone Imagery
  7. 2026JEDI: JEPA-to-Edge Distillation for Efficient Cropland Segmentation from Satellite Imagery
  8. 2026SkyVLaM: Multimodal Large Language Model for UAV Video Understanding in Remote Sensing