Awesome Papers

Papers

Unsupervised Feature Learning Via Non-parametric Instance-level Discrimination (2018)
Zhirong Wu, Yuanjun Xiong, Stella Yu, et al.
25.66
Cross-batch Memory For Embedding Learning (2019)
Xun Wang, Haozhi Zhang, Weilin Huang, et al.
22.13
Sampling Matters In Deep Embedding Learning (2017)
Chao-Yuan Wu, R. Manmatha, Alexander J. Smola, et al.
20.43
Bsnet: Bi-similarity Network For Few-shot Fine-grained Image Classification (2020)
Xiaoxu Li, Jijie Wu, Zhuo Sun, et al.
20.42
No Fuss Distance Metric Learning Using Proxies (2017)
Yair Movshovitz-Attias, Alexander Toshev, Thomas K. Leung, et al.
20.03
Unsupervised Embedding Learning Via Invariant And Spreading Instance Feature (2019)
Mang Ye, Xu Zhang, Pong C. Yuen, et al.
19.76
Contrastive Learning With Stronger Augmentations (2021)
Xiao Wang, Guo-Jun Qi
19.61
Selective Convolutional Descriptor Aggregation For Fine-grained Image Retrieval (2016)
Xiu-Shen Wei, Jian-Hao Luo, Jianxin Wu, et al.
19.37
Learning With Average Precision: Training Image Retrieval With A Listwise Loss (2019)
Jerome Revaud, Jon Almazan, Rafael Sampaio de Rezende, et al.
18.86
With A Little Help From My Friends: Nearest-neighbor Contrastive Learning Of Visual Representations (2021)
Debidatta Dwibedi, Yusuf Aytar, Jonathan Tompson, et al.
18.76
Learning Metrics From Teachers: Compact Networks For Image Embedding (2019)
Lu Yu, Vacit Oguz Yazici, Xialei Liu, et al.
18.74
Few-shot Object Counting With Similarity-aware Feature Enhancement (2022)
Zhiyuan You, Kai Yang, Wenhan Luo, et al.
18.62
A Decade Survey Of Content Based Image Retrieval Using Deep Learning (2020)
Shiv Ram Dubey
18.33
Deep Metric Learning With Hierarchical Triplet Loss (2018)
Weifeng Ge, Weilin Huang, Dengke Dong, et al.
18.20
Revisiting Oxford And Paris: Large-scale Image Retrieval Benchmarking (2018)
Filip Radenović, Ahmet Iscen, Giorgos Tolias, et al.
17.97
Hyperbolic Image Embeddings (2019)
Valentin Khrulkov, Leyla Mirvakhabova, Evgeniya Ustinova, et al.
17.91
Wireless Image Retrieval At The Edge (2020)
Mikolaj Jankowski, Deniz Gunduz, Krystian Mikolajczyk
17.82
Optimizing Rank-based Metrics With Blackbox Differentiation (2019)
Michal Rolínek, Vít Musil, Anselm Paulus, et al.
17.35
Deep Metric Learning Via Facility Location (2016)
Hyun Oh Song, Stefanie Jegelka, Vivek Rathod, et al.
17.16
Pseudo-supervised Deep Subspace Clustering (2021)
Juncheng Lv, Zhao Kang, Xiao Lu, et al.
16.10
Attention-based Ensemble For Deep Metric Learning (2018)
Wonsik Kim, Bhavya Goyal, Kunal Chawla, et al.
15.90
Towards Interpretable Deep Metric Learning With Structural Matching (2021)
Wenliang Zhao, Yongming Rao, Ziyi Wang, et al.
15.87
Efficient Diffusion On Region Manifolds: Recovering Small Objects With Compact CNN Representations (2016)
Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, et al.
15.83
Diffusion Art Or Digital Forgery? Investigating Data Replication In Diffusion Models (2022)
Gowthami Somepalli, Vasu Singla, Micah Goldblum, et al.
15.75
Cross-domain Visual Matching Via Generalized Similarity Measure And Feature Learning (2016)
Liang Lin, Guangrun Wang, Wangmeng Zuo, et al.
15.54
PADS: Policy-adapted Sampling For Visual Similarity Learning (2020)
Karsten Roth, Timo Milbich, Björn Ommer
15.46
Boosting Vision Transformers For Image Retrieval (2022)
Chull Hwan Song, Jooyoung Yoon, Shunghyun Choi, et al.
15.28
Learning Robust Visual-semantic Embeddings (2017)
Yao-Hung Hubert Tsai, Liang-Kang Huang, Ruslan Salakhutdinov
15.22
Probability Weighted Compact Feature For Domain Adaptive Retrieval (2020)
Fuxiang Huang, Lei Zhang, Yang Yang, et al.
15.19
Smooth-ap: Smoothing The Path Towards Large-scale Image Retrieval (2020)
Andrew Brown, Weidi Xie, Vicky Kalogeiton, et al.
15.06
Conditional Similarity Networks (2016)
Andreas Veit, Serge Belongie, Theofanis Karaletsos
15.06
Improved Embeddings With Easy Positive Triplet Mining (2019)
Hong Xuan, Abby Stylianou, Robert Pless
15.06
Revisiting Metric Learning For Few-shot Image Classification (2019)
Xiaomeng Li, Lequan Yu, Chi-Wing Fu, et al.
14.90
Darkrank: Accelerating Deep Metric Learning Via Cross Sample Similarities Transfer (2017)
Yuntao Chen, Naiyan Wang, Zhaoxiang Zhang
14.87
Hard Negative Examples Are Hard, But Useful (2020)
Hong Xuan, Abby Stylianou, Xiaotong Liu, et al.
14.76
Proxynca++: Revisiting And Revitalizing Proxy Neighborhood Component Analysis (2020)
Eu Wern Teh, Terrance Devries, Graham W. Taylor
14.69
Enhancing Remote Sensing Image Retrieval With Triplet Deep Metric Learning Network (2019)
Rui Cao, Qian Zhang, Jiasong Zhu, et al.
14.58
Face Clustering: Representation And Pairwise Constraints (2017)
Yichun Shi, Charles Otto, Anil K. Jain
14.58
Represent, Compare, And Learn: A Similarity-aware Framework For Class-agnostic Counting (2022)
Min Shi, Hao Lu, Chen Feng, et al.
14.58
Deep Metric Learning With BIER: Boosting Independent Embeddings Robustly (2018)
Michael Opitz, Georg Waltner, Horst Possegger, et al.
14.55
Deep Metric Learning Beyond Binary Supervision (2019)
Sungyeon Kim, Minkyo Seo, Ivan Laptev, et al.
14.39
Divide And Conquer The Embedding Space For Metric Learning (2019)
Artsiom Sanakoyeu, Vadim Tschernezki, Uta Büchler, et al.
14.39
A Compact Embedding For Facial Expression Similarity (2018)
Raviteja Vemulapalli, Aseem Agarwala
14.39
Visual Explanation For Deep Metric Learning (2019)
Sijie Zhu, Taojiannan Yang, Chen Chen
14.36
Mining On Manifolds: Metric Learning Without Labels (2018)
Ahmet Iscen, Giorgos Tolias, Yannis Avrithis, et al.
14.31
Integrating Language Guidance Into Vision-based Deep Metric Learning (2022)
Karsten Roth, Oriol Vinyals, Zeynep Akata
14.04
Phase Diagram Of Restricted Boltzmann Machines And Generalised Hopfield Networks With Arbitrary Priors (2017)
Adriano Barra, Giuseppe Genovese, Peter Sollich, et al.
14.02
Deep Randomized Ensembles For Metric Learning (2018)
Hong Xuan, Richard Souvenir, Robert Pless
13.97
Learning Similarity Conditions Without Explicit Supervision (2019)
Reuben Tan, Mariya I. Vasileva, Kate Saenko, et al.
13.93
Introspective Deep Metric Learning (2023)
Chengkun Wang, Wenzhao Zheng, Zheng Zhu, et al.
13.85