mlsanityData to 7 Oct 2026

Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation

arXiv 2405.06228 ↗First posted 10 May 2024cs.CVcited by 25

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Abstract (arXiv)

Semantic segmentation is an important task for numerous applications but it is still quite challenging to achieve advanced performance with limited computational costs. In this paper, we present CGRSeg, an efficient yet competitive segmentation framework based on context-guided spatial feature reconstruction. A Rectangular Self-Calibration Module is carefully designed for spatial feature reconstruction and pyramid context extraction. It captures the axial global context in both horizontal and vertical directions to explicitly model rectangular key areas. A shape self-calibration function is designed to make the key areas closer to foreground objects. Besides, a lightweight Dynamic Prototype Guided head is proposed to improve the classification of foreground objects by explicit class embedding. Our CGRSeg is extensively evaluated on ADE20K, COCO-Stuff, and Pascal Context benchmarks, and achieves state-of-the-art semantic performance. Specifically, it achieves 43.6% mIoU on ADE20K with only 4.0 GFLOPs, which is 0.9% and 2.5% mIoU better than SeaFormer and SegNeXt but with about 38.0% fewer GFLOPs. Code is available at https://github.com/nizhenliang/CGRSeg.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). Builds on 38 of its 44 references that are in the map. First posted on arXiv 10 May 2024.

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38 of 44 references.

References · 38

  1. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,845
  2. 2022A ConvNet for the 2020scited by 3,545
  3. 2016DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFscited by 3,239
  4. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,210
  5. 2021SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformerscited by 2,923
  6. 2016Pyramid Scene Parsing Networkcited by 2,472
  7. 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,338
  8. 2017Non-local Neural Networkscited by 2,290
  9. 2017Rethinking Atrous Convolution for Semantic Image Segmentationcited by 2,154
  10. 2019Deep High-Resolution Representation Learning for Visual Recognitioncited by 1,417
  11. 2020Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformerscited by 1,368
  12. 2021Per-Pixel Classification is Not All You Need for Semantic Segmentationcited by 1,148
26 more
  1. 2018Dual Attention Network for Scene Segmentationcited by 1,001
  2. 2016COCO-Stuff: Thing and Stuff Classes in Contextcited by 858
  3. 2018CCNet: Criss-Cross Attention for Semantic Segmentationcited by 717
  4. 2018BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentationcited by 645
  5. 2019Segmentation Transformer: Object-Contextual Representations for Semantic Segmentationcited by 573
  6. 2019GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyondcited by 331
  7. 2018Context Encoding for Semantic Segmentationcited by 289
  8. 2019Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentationcited by 258
  9. 2022SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentationcited by 252
  10. 2021Exploring Cross-Image Pixel Contrast for Semantic Segmentationcited by 242
  11. 2021Coordinate Attention for Efficient Mobile Network Designcited by 239
  12. 2019Expectation-Maximization Attention Networks for Semantic Segmentationcited by 147
  13. 2022Rethinking Semantic Segmentation: A Prototype Viewcited by 140
  14. 2018Gather-Excite: Exploiting Feature Context in Convolutional Neural Networkscited by 138
  15. 2021Rethinking BiSeNet For Real-time Semantic Segmentationcited by 124
  16. 2022Rethinking Vision Transformers for MobileNet Size and Speedcited by 121
  17. 2022SegViT: Semantic Segmentation with Plain Vision Transformerscited by 105
  18. 2019DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentationcited by 100
  19. 2023InceptionNeXt: When Inception Meets ConvNeXtcited by 84
  20. 2022TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentationcited by 82
  21. 2021Is Attention Better Than Matrix Decomposition?cited by 75
  22. 2024PEM: Prototype-based Efficient MaskFormer for Image Segmentationcited by 35
  23. 2023CLUSTSEG: Clustering for Universal Segmentationcited by 32
  24. 2023SeaFormer++: Squeeze-enhanced Axial Transformer for Mobile Visual Recognitioncited by 18
  25. 2021Efficient Self-Ensemble for Semantic Segmentationcited by 16
  26. 2023Low-Resolution Self-Attention for Semantic Segmentationcited by 12

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 13; 2026: 9.

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  1. 2025Sa2VA: Marrying SAM2 with MLLM for Dense Grounded Understanding of Images and Videoscited by 154
  2. 2024SegMAN: Omni-scale Context Modeling with State Space Models and Local Attention for Semantic Segmentationcited by 31
  3. 2024Deformable Mamba for Wide Field of View Segmentationcited by 7
  4. 2025Revisiting Efficient Semantic Segmentation: Learning Offsets for Better Spatial and Class Feature Alignmentcited by 5
  5. 2026Refining Context-Entangled Content Segmentation via Curriculum Selection and Anti-Curriculum Promotioncited by 5
  6. 2025MambaSeg: Harnessing Mamba for Accurate and Efficient Image-Event Semantic Segmentationcited by 4
  7. 2026Diffusion Model as a Generalist Segmentation Learnercited by 4
  8. 2025FMLGS: Fast Multilevel Language Embedded Gaussians for Part-level Interactive Agentscited by 3
  9. 2025MaSS13K: A Matting-level Semantic Segmentation Benchmarkcited by 2
  10. 2025Semantics versus Identity: A Divide-and-Conquer Approach towards Adjustable Medical Image De-Identificationcited by 2
  11. 2024SLTNet: Efficient Event-based Semantic Segmentation with Spike-driven Lightweight Transformer-based Networkscited by 1
  12. 2025ContextFormer: Redefining Efficiency in Semantic Segmentationcited by 1
13 more
  1. 2025A2Mamba: Attention-augmented State Space Models for Visual Recognitioncited by 1
  2. 2025Segment Any Vehicle: Semantic and Visual Context Driven SAM and A Benchmarkcited by 1
  3. 2026Restoration Adaptation for Semantic Segmentation on Low Quality Imagescited by 1
  4. 2026HyperVision: A Channel-Adaptive Ground-Based Hyperspectral Vision Pre-trained Backbonecited by 1
  5. 2025Teacher Encoder-Student Decoder Denoising Guided Segmentation Network for Anomaly Detectioncited by 0
  6. 2025Masked Representation Modeling for Domain-Adaptive Segmentationcited by 0
  7. 2025Intelligent Communication Mixture-of-Experts Boosted-Medical Image Segmentation Foundation Modelcited by 0
  8. 2025WaveSeg: Enhancing Segmentation Precision via High-Frequency Prior and Mamba-Driven Spectrum Decompositioncited by 0
  9. 2026UAV-DETR: DETR for Anti-Drone Target Detectioncited by 0
  10. 2026Chatting about Upper-Body Expressive Human Pose and Shape Estimationcited by 0
  11. 2026Thresholded Cross-Attention for Reliable Intensity-Chromaticity Fusion in Low-Light Image Enhancementcited by 0
  12. 2026DishSeg24k: A Large-Scale Benchmark for Food Segmentation with Stochastic Expert Decodingcited by 0
  13. 2026CoordFormer: Give Me Any Coordinates and I Will Give You Labelscited by 0