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Fine-grained object retrieval aims to learn discriminative representation to retrieve visually similar objects.
3D Object Representations for Fine-Grained Categorization
Krause, J.; Stark, M.; Deng, J.; and Fei-Fei, L. 2013 · 2013
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Fine-Grained Visual Classification of Aircraft
Maji, S.; Rahtu, E.; Kannala, J.; Blaschko, M. B.; and Vedaldi, A. 2013 · 2013
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Bird Species Categorization Using Pose Normalized Deep Convolutional Nets
Branson, S.; Horn, G. V.; Belongie, S. J.; and Perona, P. 2014 · 2014
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Learning visual similarity for product design with convolutional neural networks
Bell, S.; and Bala, K. 2015 · 2015
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Deep Residual Learning for Image Recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
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Deep Metric Learning via Lifted Structured Feature Embedding
Song, H. O.; Xiang, Y.; Jegelka, S.; and Savarese, S. 2016 · 2016
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Rethinking the Inception Architecture for Computer Vision
Szegedy, C.; Vanhoucke, V.; Ioffe, S.; Shlens, J.; and Wojna, Z. 2016 · 2016
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Selective Convolutional Descriptor Aggregation for Fine-Grained Image Retrieval
Wei, X.; Luo, J.; Wu, J.; and Zhou, Z. 2017 · 2017
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Squeeze-and-Excitation Networks
Hu, J.; Shen, L.; and Sun, G. 2018 · 2018
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Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net
Pan, X.; Luo, P.; Shi, J.; and Tang, X. 2018 · 2018
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Centralized Ranking Loss with Weakly Supervised Localization for Fine-Grained Object Retrieval
Zheng, X.; Ji, R.; Sun, X.; Wu, Y.; Huang, F.; and Yang, Y. 2018 · 2018
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Multi-Similarity Loss With General Pair Weighting for Deep Metric Learning
Wang, X.; Han, X.; Huang, W.; Dong, D.; and Scott, M. R. 2019a · 2019
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Accurate And Fast Fine-Grained Image Classification via Discriminative Learning
Wang, Z.; Wang, S.; Zhang, P.; Li, H.; and Liu, B. 2019b · 2019
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Weakly Supervised Fine-grained Image Classification via Correlation-guided Discriminative Learning
Wang, Z.; Wang, S.; Zhang, P.; Li, H.; Zhong, W.; and Li, J. 2019c · 2019
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Towards Optimal Fine Grained Retrieval via Decorrelated Centralized Loss with Normalize-Scale Layer
Zheng, X.; Ji, R.; Sun, X.; Zhang, B.; Wu, Y.; and Huang, F. 2019 · 2019
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Fast Context Adaptation via Meta-Learning
Zintgraf, L. M.; Shiarlis, K.; Kurin, V.; Hofmann, K.; and Whiteson, S. 2019 · 2019
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A Unifying Mutual Information View of Metric Learning: Cross-Entropy vs. Pairwise Losses
Boudiaf, M.; Rony, J.; Ziko, I. M.; Granger, E.; Pedersoli, M.; Piantanida, P.; and Ayed, I. B. 2020 · 2020
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How Can We Know What Language Models Know
Jiang, Z.; Xu, F. F.; Araki, J.; and Neubig, G. 2020 · 2020
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ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis
Teh, E. W. 2020 · 2020
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Category-specific Semantic Coherency Learning for Fine-grained Image Recognition
Wang, S.; Wang, Z.; Li, H.; and Ouyang, W. 2020a · 2020
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Graph-Propagation Based Correlation Learning for Weakly Supervised Fine-Grained Image Classification
Keypoint-Aligned Embeddings for Image Retrieval and Re-identification
Moskvyak, O.; Maire, F.; Dayoub, F.; and Baktashmotlagh, M. 2021 · 2021
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Learning Transferable Visual Models From Natural Language Supervision
Radford, A.; Kim, J. W.; Hallacy, C.; Ramesh, A.; Goh, G.; Agarwal, S.; Sastry, G.; Askell, A.; Mishkin, P.; Clark, J.; Krueger, G.; and Sutskever, I. 2021 · 2021
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Simultaneous Similarity-based Self-Distillation for Deep Metric Learning
Roth, K.; Milbich, T.; Ommer, B.; Cohen, J. P.; and Ghassemi, M. 2021 · 2021
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Learning Intra-Batch Connections for Deep Metric Learning
Seidenschwarz, J. D. 2021 · 2021
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Dynamic Position-aware Network for Fine-grained Image Recognition
Wang, S.; Li, H.; Wang, Z.; and Ouyang, W. 2021 · 2021
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CPT: Colorful Prompt Tuning for Pre-trained Vision-Language Models
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Wang, Z.; Wang, S.; Li, H.; Dou, Z.; and Li, J. 2020b · 2020
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Weakly Supervised Fine-Grained Image Classification via Guassian Mixture Model Oriented Discriminative Learning
Wang, Z.; Wang, S.; Yang, S.; Li, H.; Li, J.; and Li, Z. 2020c · 2020
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MetricOpt: Learning To Optimize Black-Box Evaluation Metrics
Huang, C.; Zhai, S.; Guo, P.; and Susskind, J. M. 2021 · 2021
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Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
Jia, C.; Yang, Y.; Xia, Y.; Chen, Y.; Parekh, Z.; Pham, H.; Le, Q. V.; Sung, Y.; Li, Z.; and Duerig, T. 2021 · 2021
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MDETR - Modulated Detection for End-to-End Multi-Modal Understanding
Kamath, A.; Singh, M.; LeCun, Y.; Synnaeve, G.; Misra, I.; and Carion, N. 2021 · 2021
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Embedding Transfer With Label Relaxation for Improved Metric Learning
Kim, S.; Kim, D.; Cho, M.; and Kwak, S. 2021 · 2021
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Learning with Memory-based Virtual Classes for Deep Metric Learning
Ko, B.; and Gu, G. 2021 · 2021
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Yao, Y.; Zhang, A.; Zhang, Z.; Liu, Z.; Chua, T.; and Sun, M. 2021 · 2021
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Hard Decorrelated Centralized Loss for fine-grained image retrieval
Zeng, X.; Liu, S.; Wang, X.; Zhang, Y.; Chen, K.; and Li, D. 2021 · 2021
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Deep Compositional Metric Learning
Zheng, W.; Wang, C.; Lu, J.; and Zhou, J. 2021a · 2021
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Deep Relational Metric Learning
Zheng, W.; Zhang, B.; Lu, J.; and Zhou, J. 2021b · 2021
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OhMG: Zero-shot Open-vocabulary Human Motion Generation
Lin, J.; Chang, J.; Liu, L.; Li, G.; Lin, L.; Tian, Q.; and Chen, C. W. 2022 · 2022
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Prompt-Matched Semantic Segmentation
Liu, L.; Yu, B. X. B.; Chang, J.; Tian, Q.; and Chen, C. W. 2022 · 2022
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Pro-tuning: Unified Prompt Tuning for Vision Tasks
Nie, X.; Ni, B.; Chang, J.; Meng, G.; Huo, C.; Zhang, Z.; Xiang, S.; Tian, Q.; and Pan, C. 2022 · 2022
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Category-Specific Nuance Exploration Network for Fine-Grained Object Retrieval
Wang, S.; Wang, Z.; Li, H.; and Ouyang, W. 2022a · 2022
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Towards a Unified View on Visual Parameter-Efficient Transfer Learning
Yu, B. X. B.; Chang, J.; Liu, L.; Tian, Q.; and Chen, C. W. 2022 · 2022
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Spatial Transformer Networks
Jaderberg, M.; Simonyan, K.; Zisserman, A.; and Kavukcuoglu, K. 2015 · 2025
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