mlsanityData to 14 Oct 2026

Graph Distillation for Action Detection with Privileged Modalities

arXiv 1712.00108 ↗First posted 30 Nov 2017cs.CVcited by 35

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Abstract (arXiv)

We propose a technique that tackles action detection in multimodal videos under a realistic and challenging condition in which only limited training data and partially observed modalities are available. Common methods in transfer learning do not take advantage of the extra modalities potentially available in the source domain. On the other hand, previous work on multimodal learning only focuses on a single domain or task and does not handle the modality discrepancy between training and testing. In this work, we propose a method termed graph distillation that incorporates rich privileged information from a large-scale multimodal dataset in the source domain, and improves the learning in the target domain where training data and modalities are scarce. We evaluate our approach on action classification and detection tasks in multimodal videos, and show that our model outperforms the state-of-the-art by a large margin on the NTU RGB+D and PKU-MMD benchmarks. The code is released at http://alan.vision/eccv18_graph/.

Key facts. Cited by 35 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Nov 2017.

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Citing papers per year: 2021: 12; 2022: 4; 2023: 9; 2024: 6; 2025: 1; 2026: 3.

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  1. 2021Ego-Exo: Transferring Visual Representations from Third-person to First-person Videoscited by 99
  2. 2023Decoupled Multimodal Distilling for Emotion Recognitioncited by 76
  3. 2022Towards Good Practices for Missing Modality Robust Action Recognitioncited by 54
  4. 2023On Uni-Modal Feature Learning in Supervised Multi-Modal Learningcited by 53
  5. 2022The Modality Focusing Hypothesis: Towards Understanding Crossmodal Knowledge Distillationcited by 44
  6. 2021VPN++: Rethinking Video-Pose embeddings for understanding Activities of Daily Livingcited by 35
  7. 2021Learning an Augmented RGB Representation with Cross-Modal Knowledge Distillation for Action Detectioncited by 32
  8. 2021Data-Free Knowledge Transfer: A Surveycited by 31
  9. 2023Robust Multimodal Learning with Missing Modalities via Parameter-Efficient Adaptationcited by 29
  10. 2022VALHALLA: Visual Hallucination for Machine Translationcited by 27
  11. 2024Cross-Modal Prototype based Multimodal Federated Learning under Severely Missing Modalitycited by 21
  12. 2021ViewCLR: Learning Self-supervised Video Representation for Unseen Viewpointscited by 20
23 more
  1. 2022Respecting Transfer Gap in Knowledge Distillationcited by 18
  2. 2021DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrievalcited by 17
  3. 2021Fusion-GCN: Multimodal Action Recognition using Graph Convolutional Networkscited by 15
  4. 2023LAC: Latent Action Composition for Skeleton-based Action Segmentationcited by 15
  5. 2024AMFD: Distillation via Adaptive Multimodal Fusion for Multispectral Pedestrian Detectioncited by 15
  6. 2021Dealing with Missing Modalities in the Visual Question Answer-Difference Prediction Task through Knowledge Distillationcited by 14
  7. 2023Decomposed Cross-modal Distillation for RGB-based Temporal Action Detectioncited by 12
  8. 2021Distilling and Transferring Knowledge via cGAN-generated Samples for Image Classification and Regressioncited by 10
  9. 2021Cross-Modal Knowledge Distillation Method for Automatic Cued Speech Recognitioncited by 8
  10. 2023Graph-based Knowledge Distillation: A survey and experimental evaluationcited by 6
  11. 2024MTMMC: A Large-Scale Real-World Multi-Modal Camera Tracking Benchmarkcited by 5
  12. 2024Self-Supervised Skeleton-Based Action Representation Learning: A Benchmark and Beyondcited by 5
  13. 2023One-stage Modality Distillation for Incomplete Multimodal Learningcited by 4
  14. 2024Reconstruct before Query: Continual Missing Modality Learning with Decomposed Prompt Collaborationcited by 4
  15. 2021Distillation of Human-Object Interaction Contexts for Action Recognitioncited by 1
  16. 2023DMT: Comprehensive Distillation with Multiple Self-supervised Teacherscited by 1
  17. 2024MVKTrans: Multi-View Knowledge Transfer for Robust Multiomics Classificationcited by 1
  18. 2026Decoupled Hierarchical Distillation for Multimodal Emotion Recognitioncited by 1
  19. 2021Bridging the gap between Human Action Recognition and Online Action Detectioncited by 0
  20. 2023Recursive Distillation for Open-Set Distributed Robot Localizationcited by 0
  21. 2025CoMAD: A Multiple-Teacher Self-Supervised Distillation Frameworkcited by 0
  22. 2026T-MOR: Learning Motion-Aware Skeleton Representations for Human Action Recognitioncited by 0
  23. 2026Distill What RGB Can Recover: Privileged 3D Evidence for RGB-Only Vision-Language Modelscited by 0