mlsanityData to 7 Oct 2026

Collaborative Intelligence: Challenges and Opportunities

arXiv 2102.06841 ↗First posted 13 Feb 2021eess.IV cs.CVcited by 18

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Abstract (arXiv)

This paper presents an overview of the emerging area of collaborative intelligence (CI). Our goal is to raise awareness in the signal processing community of the challenges and opportunities in this area of growing importance, where key developments are expected to come from signal processing and related disciplines. The paper surveys the current state of the art in CI, with special emphasis on signal processing-related challenges in feature compression, error resilience, privacy, and system-level design.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 27 of its 44 references that are in the map. First posted on arXiv 13 Feb 2021.

Builds on

27 of 44 references.

References · 27

  1. 2016YOLO9000: Better, Faster, Strongercited by 1,429
  2. 2017Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semanticscited by 1,345
  3. 2017Learning multiple visual domains with residual adapterscited by 553
  4. 2018End-to-End Multi-Task Learning with Attentioncited by 533
  5. 2016Cross-stitch Networks for Multi-task Learningcited by 466
  6. 2018Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Accelerationcited by 365
  7. 2018LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networkscited by 272
  8. 2019Residual Non-local Attention Networks for Image Restorationcited by 236
  9. 2015Accelerating Very Deep Convolutional Networks for Classification and Detectioncited by 109
  10. 2017Incremental Learning Through Deep Adaptationcited by 108
  11. 2019BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systemscited by 94
  12. 2017One Model To Learn Them Allcited by 86
15 more
  1. 2020Video Coding for Machines: A Paradigm of Collaborative Compression and Intelligent Analyticscited by 80
  2. 2018JointDNN: An Efficient Training and Inference Engine for Intelligent Mobile Cloud Computing Servicescited by 79
  3. 2017Towards Effective Low-bitwidth Convolutional Neural Networkscited by 76
  4. 2019Branched Multi-Task Networks: Deciding What Layers To Sharecited by 76
  5. 2020Privacy in Deep Learning: A Surveycited by 70
  6. 2016A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Taskscited by 62
  7. 2018Deep feature compression for collaborative object detectioncited by 48
  8. 2020Towards Analysis-friendly Face Representation with Scalable Feature and Texture Compressioncited by 28
  9. 2017Compact Descriptors for Video Analysis: the Emerging MPEG Standardcited by 20
  10. 2018Multi-Task Zipping via Layer-wise Neuron Sharingcited by 20
  11. 2019Multi-task learning with compressible features for Collaborative Intelligencecited by 20
  12. 2018Near-Lossless Deep Feature Compression for Collaborative Intelligencecited by 17
  13. 2015Learning Multiple Tasks with Multilinear Relationship Networkscited by 11
  14. 2018Unifying and Merging Well-trained Deep Neural Networks for Inference Stagecited by 8
  15. 2019Towards Collaborative Intelligence Friendly Architectures for Deep Learningcited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 4; 2023: 4; 2024: 2; 2025: 2; 2026: 1.

18 papers.

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  1. 2022Image Coding for Machines with Omnipotent Feature Learningcited by 31
  2. 2021Video Coding for Machine: Compact Visual Representation Compression for Intelligent Collaborative Analyticscited by 11
  3. 2022Decentralized Low-Latency Collaborative Inference via Ensembles on the Edgecited by 9
  4. 2021Lightweight Compression of Intermediate Neural Network Features for Collaborative Intelligencecited by 7
  5. 2021Single-Training Collaborative Object Detectors Adaptive to Bandwidth and Computationcited by 6
  6. 2023Slimmable Encoders for Flexible Split DNNs in Bandwidth and Resource Constrained IoT Systemscited by 3
  7. 2022Privacy-Preserving Feature Coding for Machinescited by 2
  8. 2023Conditional and Residual Methods in Scalable Coding for Humans and Machinescited by 2
  9. 2023SplitFed resilience to packet loss: Where to split, that is the questioncited by 2
  10. 2022License Plate Privacy in Collaborative Visual Analysis of Traffic Scenescited by 1
  11. 2024Scalable Human-Machine Point Cloud Compressioncited by 1
  12. 2024Optimizing Split Points for Error-Resilient SplitFed Learningcited by 1
6 more
  1. 2025Enabling Next-Generation Consumer Experience with Feature Coding for Machinescited by 1
  2. 2025Feature Coding for Scalable Machine Visioncited by 1
  3. 2021Error Resilient Collaborative Intelligence via Low-Rank Tensor Completioncited by 0
  4. 2021DFTS2: Simulating Deep Feature Transmission Over Packet Loss Channelscited by 0
  5. 2023Grad-FEC: Unequal Loss Protection of Deep Features in Collaborative Intelligencecited by 0
  6. 2026Trainable Bitwise Soft Quantization for Input Feature Compressioncited by 0