mlsanityData to 14 Oct 2026

Distributed Semantic Segmentation With Improved Rate-Distortion Trade-Off

arXiv 2608.28684 ↗First posted 26 Aug 2026cs.CV cs.LGcited by 0

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Abstract (arXiv)

Distributed deep neural networks (DNNs) for dense perception tasks such as semantic segmentation execute an encoder DNN on edge devices, and a decoder DNN typically on a large-scale cloud platform with a particular constraint on transmission bitrate. Recent works employ source codecs to enable bitrate-efficient transmission between the edge device and the cloud. However, as these approaches are typically bound to a particular type of source codec and alternative network architectures are often not explored, this results in a suboptimal rate-distortion (RD) trade-off in the low-bitrate regime. In this work, we propose two novel source codecs that textitenable extremely low bitrates, while improving RD performance. We demonstrate the effectiveness of our proposed source codecs by achieving state-of-the-art performance in distributed semantic segmentation at below 0.2 (0.03) bits per pixel, measured using the mean intersection-over-union metric on ADE20K (Cityscapes).

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 34 of its 50 references that are in the map. First posted on arXiv 26 Aug 2026.

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34 of 50 references.

References · 34

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  3. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  4. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  5. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,859
  6. 2016The Cityscapes Dataset for Semantic Urban Scene Understandingcited by 4,444
  7. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,223
  8. 2021SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformerscited by 2,940
  9. 2020Transformers are RNNs: Fast Autoregressive Transformers with Linear Attentioncited by 2,022
  10. 2017Deformable Convolutional Networkscited by 1,488
  11. 2015SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentationcited by 1,487
  12. 2019Deep High-Resolution Representation Learning for Visual Recognitioncited by 1,420
22 more
  1. 2015Multi-Scale Context Aggregation by Dilated Convolutionscited by 1,133
  2. 2018Variational image compression with a scale hyperpriorcited by 935
  3. 2016End-to-end Optimized Image Compressioncited by 696
  4. 2018Joint Autoregressive and Hierarchical Priors for Learned Image Compressioncited by 664
  5. 2014Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFscited by 554
  6. 2015Learning Deconvolution Network for Semantic Segmentationcited by 365
  7. 2020CompressAI: a PyTorch library and evaluation platform for end-to-end compression researchcited by 276
  8. 2020Channel-wise Autoregressive Entropy Models for Learned Image Compressioncited by 264
  9. 2013OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networkscited by 224
  10. 2023Learned Image Compression with Mixed Transformer-CNN Architecturescited by 211
  11. 2014Hypercolumns for Object Segmentation and Fine-grained Localizationcited by 128
  12. 2019BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systemscited by 95
  13. 2018Towards Image Understanding from Deep Compression without Decodingcited by 52
  14. 2014Convolutional Feature Masking for Joint Object and Stuff Segmentationcited by 41
  15. 2020Neural Compression and Filtering for Edge-assisted Real-time Object Detection in Challenged Networkscited by 28
  16. 2022BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computingcited by 28
  17. 2025Learned Image Compression with Hierarchical Progressive Context Modelingcited by 21
  18. 2022SC2 Benchmark: Supervised Compression for Split Computingcited by 15
  19. 2022Semantic Segmentation in Learned Compressed Domaincited by 10
  20. 2024Bjontegaard Delta (BD): A Tutorial Overview of the Metric, Evolution, Challenges, and Recommendationscited by 6
  21. 2024Distributed Semantic Segmentation with Efficient Joint Source and Task Decodingcited by 4
  22. 2025An Efficient Semantic Segmentation Decoder for In-Car or Distributed Applicationscited by 1

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