mlsanityData to 7 Oct 2026

Feedforward semantic segmentation with zoom-out features

arXiv 1412.0774 ↗First posted 2 Dec 2014cs.CVcited by 21

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Abstract (arXiv)

We introduce a purely feed-forward architecture for semantic segmentation. We map small image elements (superpixels) to rich feature representations extracted from a sequence of nested regions of increasing extent. These regions are obtained by "zooming out" from the superpixel all the way to scene-level resolution. This approach exploits statistical structure in the image and in the label space without setting up explicit structured prediction mechanisms, and thus avoids complex and expensive inference. Instead superpixels are classified by a feedforward multilayer network. Our architecture achieves new state of the art performance in semantic segmentation, obtaining 64.4% average accuracy on the PASCAL VOC 2012 test set.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Dec 2014.

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Citing papers per year: 2018: 1; 2019: 0; 2020: 0; 2021: 8; 2022: 5; 2023: 4; 2024: 2; 2025: 0; 2026: 1.

21 papers.

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  1. 2022Unsupervised Hierarchical Semantic Segmentation with Multiview Cosegmentation and Clustering Transformerscited by 39
  2. 2023Structural and Statistical Texture Knowledge Distillation for Semantic Segmentationcited by 34
  3. 2023ProtoSeg: Interpretable Semantic Segmentation with Prototypical Partscited by 33
  4. 2023Semantic Image Segmentation: Two Decades of Researchcited by 26
  5. 2023Large Separable Kernel Attention: Rethinking the Large Kernel Attention Design in CNNcited by 25
  6. 2022Neural Neighbor Style Transfercited by 23
  7. 2022Multi-Class Segmentation from Aerial Views using Recursive Noise Diffusioncited by 8
  8. 2021The Overlooked Classifier in Human-Object Interaction Recognitioncited by 7
  9. 2021Superevents: Towards Native Semantic Segmentation for Event-based Camerascited by 6
  10. 2021Superpixel-based Refinement for Object Proposal Generationcited by 4
  11. 2018MoE-SPNet: A Mixture-of-Experts Scene Parsing Networkcited by 3
  12. 2026FaceRefiner: High-Fidelity Facial Texture Refinement with Differentiable Rendering-based Style Transfercited by 3
9 more
  1. 2021Learning Class-Agnostic Pseudo Mask Generation for Box-Supervised Semantic Segmentationcited by 2
  2. 2021A Novel Upsampling and Context Convolution for Image Semantic Segmentationcited by 1
  3. 2021Fast whole-slide cartography in colon cancer histology using superpixels and CNN classificationcited by 1
  4. 2021Border-SegGCN: Improving Semantic Segmentation by Refining the Border Outline using Graph Convolutional Networkcited by 1
  5. 2024Leveraging Adaptive Implicit Representation Mapping for Ultra High-Resolution Image Segmentationcited by 1
  6. 2021Detecting and Segmenting Adversarial Graphics Patterns from Imagescited by 0
  7. 2022The Overlooked Classifier in Human-Object Interaction Recognitioncited by 0
  8. 2022Data-centric AI approach to improve optic nerve head segmentation and localization in OCT en face imagescited by 0
  9. 2024Your Image is My Video: Reshaping the Receptive Field via Image-To-Video Differentiable AutoAugmentation and Fusioncited by 0