mlsanityData to 7 Oct 2026

Multi-Class Segmentation from Aerial Views using Recursive Noise Diffusion

arXiv 2212.00787 ↗First posted 1 Dec 2022cs.CVcited by 8

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Abstract (arXiv)

Semantic segmentation from aerial views is a crucial task for autonomous drones, as they rely on precise and accurate segmentation to navigate safely and efficiently. However, aerial images present unique challenges such as diverse viewpoints, extreme scale variations, and high scene complexity. In this paper, we propose an end-to-end multi-class semantic segmentation diffusion model that addresses these challenges. We introduce recursive denoising to allow information to propagate through the denoising process, as well as a hierarchical multi-scale approach that complements the diffusion process. Our method achieves promising results on the UAVid dataset and state-of-the-art performance on the Vaihingen Building segmentation benchmark. Being the first iteration of this method, it shows great promise for future improvements.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 45 of its 66 references that are in the map. First posted on arXiv 1 Dec 2022.

Builds on

45 of 66 references.

References · 45

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33 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 3; 2025: 1; 2026: 1.

8 papers.

  1. 2024Diffusion Models Meet Remote Sensing: Principles, Methods, and Perspectivescited by 27
  2. 2024DiffDet4SAR: Diffusion-based Aircraft Target Detection Network for SAR Imagescited by 15
  3. 2025Can Generative Geospatial Diffusion Models Excel as Discriminative Geospatial Foundation Models?cited by 10
  4. 2023Importance of Aligning Training Strategy with Evaluation for Diffusion Models in 3D Multiclass Segmentationcited by 5
  5. 2023A Recycling Training Strategy for Medical Image Segmentation with Diffusion Denoising Modelscited by 5
  6. 2023Single-View Height Estimation with Conditional Diffusion Probabilistic Modelscited by 1
  7. 2026COP-GEN: Latent Diffusion Transformer for Copernicus Earth Observation Datacited by 1
  8. 2024P-MSDiff: Parallel Multi-Scale Diffusion for Remote Sensing Image Segmentationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation
  2. 2023Stable Diffusion For Aerial Object Detection
  3. 2026Restrict, Don't Retrain: Inference-Time VLM Guidance for Zero-Shot Aerial Segmentation
  4. 2025Top2Ground: A Height-Aware Dual Conditioning Diffusion Model for Robust Aerial-to-Ground View Generation
  5. 2025AetherVision-Bench: An Open-Vocabulary RGB-Infrared Benchmark for Multi-Angle Segmentation across Aerial and Ground Perspectives
  6. 2026SkyVLaM: Multimodal Large Language Model for UAV Video Understanding in Remote Sensing
  7. 2026BEV-Denoise: Learning Intrinsic Noise for Accurate Bird's-Eye-View Semantic Segmentation
  8. 2025AeroReformer: Aerial Referring Transformer for UAV-based Referring Image Segmentation