mlsanityData to 7 Oct 2026

High Quality Segmentation for Ultra High-resolution Images

arXiv 2111.14482 ↗First posted 29 Nov 2021cs.CV cs.AIcited by 31

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Abstract (arXiv)

To segment 4K or 6K ultra high-resolution images needs extra computation consideration in image segmentation. Common strategies, such as down-sampling, patch cropping, and cascade model, cannot address well the balance issue between accuracy and computation cost. Motivated by the fact that humans distinguish among objects continuously from coarse to precise levels, we propose the Continuous Refinement Model~(CRM) for the ultra high-resolution segmentation refinement task. CRM continuously aligns the feature map with the refinement target and aggregates features to reconstruct these images' details. Besides, our CRM shows its significant generalization ability to fill the resolution gap between low-resolution training images and ultra high-resolution testing ones. We present quantitative performance evaluation and visualization to show that our proposed method is fast and effective on image segmentation refinement. Code will be released at https://github.com/dvlab-research/Entity.

Key facts. Cited by 31 papers in the map (data through 7 Oct 2026). Builds on 49 of its 65 references that are in the map. First posted on arXiv 29 Nov 2021.

Builds on

49 of 65 references.

References · 49

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37 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 12; 2024: 11; 2025: 3; 2026: 3.

31 papers.

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  1. 2023Segment Anything in High Qualitycited by 373
  2. 2023Transformer-Based Visual Segmentation: A Surveycited by 124
  3. 2024Bilateral Reference for High-Resolution Dichotomous Image Segmentationcited by 112
  4. 2022Learning Implicit Feature Alignment Function for Semantic Segmentationcited by 31
  5. 2023UniGS: Unified Representation for Image Generation and Segmentationcited by 29
  6. 2023SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Processcited by 28
  7. 2024Rethinking Interactive Image Segmentation with Low Latency, High Quality, and Diverse Promptscited by 22
  8. 2025SAMRefiner: Taming Segment Anything Model for Universal Mask Refinementcited by 19
  9. 2024Mamba or RWKV: Exploring High-Quality and High-Efficiency Segment Anything Modelcited by 18
  10. 2023Unite-Divide-Unite: Joint Boosting Trunk and Structure for High-accuracy Dichotomous Image Segmentationcited by 17
  11. 2023TransY-Net:Learning Fully Transformer Networks for Change Detection of Remote Sensing Imagescited by 13
  12. 2023Continuous Cross-resolution Remote Sensing Image Change Detectioncited by 8
19 more
  1. 2024Entity-NeRF: Detecting and Removing Moving Entities in Urban Scenescited by 8
  2. 2024HoloHisto: End-to-end Gigapixel WSI Segmentation with 4K Resolution Sequential Tokenizationcited by 8
  3. 2023Rethinking Evaluation Metrics of Open-Vocabulary Segmentaioncited by 7
  4. 2023AIMS: All-Inclusive Multi-Level Segmentationcited by 6
  5. 2023Stable Segment Anything Modelcited by 6
  6. 2024SOHES: Self-supervised Open-world Hierarchical Entity Segmentationcited by 6
  7. 2023Memory-Constrained Semantic Segmentation for Ultra-High Resolution UAV Imagerycited by 3
  8. 2024SU-SAM: A Simple Unified Framework for Adapting Segment Anything Model in Underperformed Scenescited by 3
  9. 2022EHSNet: End-to-End Holistic Learning Network for Large-Size Remote Sensing Image Semantic Segmentationcited by 1
  10. 2024Q2A: Querying Implicit Fully Continuous Feature Pyramid to Align Features for Medical Image Segmentationcited by 1
  11. 2024Leveraging Adaptive Implicit Representation Mapping for Ultra High-Resolution Image Segmentationcited by 1
  12. 2026Learning from Adversity: Semantic-Aware Mask Refinement through Adversarial Perturbationcited by 1
  13. 2023Elastic Interaction Energy-Informed Real-Time Traffic Scene Perceptioncited by 0
  14. 2024Resource Efficient Perception for Vision Systemscited by 0
  15. 2024Flexible Coded Distributed Convolution Computing for Enhanced Straggler Resilience and Numerical Stability in Distributed CNNscited by 0
  16. 2025Learning to Upscale 3D Segmentations in Neuroimagingcited by 0
  17. 2025Class-agnostic 3D Segmentation by Granularity-Consistent Automatic 2D Mask Trackingcited by 0
  18. 2026Adapting Vision Transformers to Ultra-High Resolution Semantic Segmentation with Relay Tokenscited by 0
  19. 2026CoordFormer: Give Me Any Coordinates and I Will Give You Labelscited by 0