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A Multi-granularity Retrieval System for Natural Language-based Vehicle Retrieval

  • Published:2022-06 Issue: Volume: Page:
  • ISSN:
  • Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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Author:

Zhang Jiacheng1,Lin Xiangru1,Jiang Minyue1,Yu Yue1,Gong Chenting1,Zhang Wei1,Tan Xiao1,Li Yingying1,Ding Errui1,Li Guanbin2

Affiliation:

1. Baidu Inc.,Department of Computer Vision Technology (VIS),China

2. Sun Yat-sen University,China

Publisher

IEEE

Reference27 articles.

1. Visual Semantic Search: Retrieving Videos via Complex Textual Queries

2. Use what you have: Video retrieval using representations from collaborative experts;liu,2019

3. Univl: A unified video and language pre-training model for multimodal understanding and generation;luo,2020

4. Clip4clip: An empirical study of clip for end to end video clip retrieval;luo,2021

5. Efficient estimation of word representations in vector space;mikolov,2013

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1. Integrating Language Guidance Into Image-Text Matching for Correcting False Negatives;IEEE Transactions on Multimedia;2024

2. Scene Retrieval in Traffic Videos with Contrastive Multimodal Learning;2023 IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI);2023-11-06

3. FindVehicle and VehicleFinder: a NER dataset for natural language-based vehicle retrieval and a keyword-based cross-modal vehicle retrieval system;Multimedia Tools and Applications;2023-08-14

4. Tracked-Vehicle Retrieval by Natural Language Descriptions with Multi-Contextual Adaptive Knowledge;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW);2023-06

5. A Unified Multi-modal Structure for Retrieving Tracked Vehicles through Natural Language Descriptions;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW);2023-06
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