research-article

Relationship-Preserving Knowledge Distillation for Zero-Shot Sketch Based Image Retrieval

Authors:

Xin LiuAuthors Info & Claims

MM '21: Proceedings of the 29th ACM International Conference on Multimedia

Pages 5473 - 5481

https://doi.org/10.1145/3474085.3475676

Published: 17 October 2021 Publication History

Abstract

Zero-shot sketch-based image retrieval is challenging for the modal gap between distributions of sketches and images and the inconsistency of label spaces during training and testing. Previous methods mitigate the modal gap by projecting sketches and images into a joint embedding space. Most of them also bridge seen and unseen classes by leveraging semantic embeddings, i.e., word vectors and hierarchical similarities. In this paper, we propose Relationship-Preserving Knowledge Distillation (RPKD) to study generalizable embeddings from the perspective of knowledge distillation bypassing the usage of semantic embeddings. In particular, we firstly distill the instance-level knowledge to preserve inter-class relationships without semantic similarities that require extra effort to collect. We also reconcile the contrastive relationships among instances between different embedding spaces, which is complementary to instance-level relationships. Furthermore, embedding-induced supervision, which measures the similarities of an instance to partial class embedding centers from the teacher, is developed to align the student's classification confidences. Extensive experiments conducted on three benchmark ZS-SBIR datasets, i.e., Sketchy, TU-Berlin, and QuickDraw, demonstrate the superiority of our proposed RPKD approach comparing to the state-of-the-art methods.

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Cited By

Gopu VDunna M(2024)Zero-Shot Sketch-Based Image Retrieval Using StyleGen and Stacked Siamese Neural NetworksJournal of Imaging10.3390/jimaging1004007910:4(79)Online publication date: 27-Mar-2024
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Ren JPeng HJiang LHao ZWu JGao SYu ZYang Q(2024)Toward Cross-Lingual Social Event Detection with Hybrid Knowledge DistillationACM Transactions on Knowledge Discovery from Data10.1145/368994818:9(1-36)Online publication date: 12-Nov-2024
https://dl.acm.org/doi/10.1145/3689948
Lyou ELee DKim JLee J(2024)Modality-Aware Representation Learning for Zero-shot Sketch-based Image Retrieval2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV57701.2024.00555(5634-5643)Online publication date: 3-Jan-2024
https://doi.org/10.1109/WACV57701.2024.00555
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Index Terms

Relationship-Preserving Knowledge Distillation for Zero-Shot Sketch Based Image Retrieval
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
        Visual content-based indexing and retrieval
2. Information systems
  1. Information retrieval

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cover image ACM Conferences

MM '21: Proceedings of the 29th ACM International Conference on Multimedia

October 2021

5796 pages

ISBN:9781450386517

DOI:10.1145/3474085

General Chairs:
Heng Tao Shen
University of Electronic Science&Technology of China, China
,
Yueting Zhuang
Zhejiang University, China
,
John R. Smith
IBM, USA
,
Program Chairs:
Yang Yang
University of Electronic Science and Technology of China, China
,
Pablo Cesar
CWI&TU Delft, The Netherlands
,
Florian Metze
FACEBOOK, Inc., USA
,
Balakrishnan Prabhakaran
University of Texas at Dallas, USA

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Published: 17 October 2021

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Sichuan Science and Technology Program
National Science Foundation of Fujian Province
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities under Project

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MM '21

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October 20 - 24, 2021

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https://doi.org/10.3390/jimaging10040079
Ren JPeng HJiang LHao ZWu JGao SYu ZYang Q(2024)Toward Cross-Lingual Social Event Detection with Hybrid Knowledge DistillationACM Transactions on Knowledge Discovery from Data10.1145/368994818:9(1-36)Online publication date: 12-Nov-2024
https://dl.acm.org/doi/10.1145/3689948
Lyou ELee DKim JLee J(2024)Modality-Aware Representation Learning for Zero-shot Sketch-based Image Retrieval2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV57701.2024.00555(5634-5643)Online publication date: 3-Jan-2024
https://doi.org/10.1109/WACV57701.2024.00555
Yuan BZhao DShi Z(2024)Learning at a Glance: Towards Interpretable Data-Limited Continual Semantic Segmentation via Semantic-Invariance ModellingIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2024.339680946:12(7909-7923)Online publication date: Dec-2024
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Yan JDeng CHuang HLiu W(2024)Causality-Invariant Interactive Mining for Cross-Modal Similarity LearningIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2024.337975246:9(6216-6230)Online publication date: Sep-2024
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Chen CYe MQi MDu B(2024)SketchTrans: Disentangled Prototype Learning With Transformer for Sketch-Photo RecognitionIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2023.333700546:5(2950-2964)Online publication date: May-2024
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Wu HWang MZhou WLi H(2024)Structure Similarity Preservation Learning for Asymmetric Image RetrievalIEEE Transactions on Multimedia10.1109/TMM.2023.332572826(4693-4705)Online publication date: 2024
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Zhou MLi BWang JZhang C(2024)Fault Diagnosis of Transmission Lines Based on Sketch Retrieval for Small Targets and Small SamplesIEEE Transactions on Industrial Informatics10.1109/TII.2024.338510220:7(9557-9567)Online publication date: Jul-2024
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He XWang JXia QLu GTang YLu H(2024)Cross-Domain Feature Semantic Calibration for Zero-Shot Sketch-Based Image Retrieval2024 IEEE International Conference on Multimedia and Expo (ICME)10.1109/ICME57554.2024.10687519(1-6)Online publication date: 15-Jul-2024
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