Not all methods use the same information from the dataset. We used codes to denote what info was used:
For additions/corrections, contact matthijs dot douze at inria dot fr.
Reference | Holidays mAP | Holidays + 1M mAP | Notes |
---|---|---|---|
Local descriptors | |||
"Hamming embedding and weak geometric consistency for large scale image search", Hervé Jégou, Matthijs Douze, Cordelia Schmid, ECCV 2008 | 75.07 | 61.8 | Introduced the dataset |
"On the burstiness of visual elements" Hervé Jégou, Matthijs Douze, Cordelia Schmid, CVPR 2009 |
QE: 83.7
QE, SP: 84.8 |
QE: 68.8
QE, SP: 77.32 | Reweight matches to take burstiness into account |
"Efficient Representation of Local Geometry for Large Scale Object Retrieval", Michal Perdoch, Ondrej Chum, Jiri Matas, CVPR 2009 | SP: 82.8 | As the method exploits the "gravity vector", the images were manually rotated into the correct orientation. | |
"Improving bag-of-features for large scale image search", Hervé Jégou, Matthijs Douze, Cordelia Schmid, IJCV 2010 |
81.3 SP: 84.8 |
62.16 SP: 75.4 | Added spatial verification, multiple assignment. Also used query expansion, but this did not improve over the simple spatial verification. |
"Learning a Fine Vocabulary", A. Mikulik, M. Perdoch, O. Chum, J. Matas, ECCV 2010 | SP,QE: 75.8 | The images were rotated to correct their orientation | |
"Exploiting descriptor distances for precise image search" Hervé Jégou; Matthijs Douze; Cordelia Schmid, INRIA research report, 2011 | QE: 86.8 | - | |
"Hello neighbor: accurate object retrieval with k-reciprocal nearest neighbors", Qin Danfeng, Stephan Gammeter, Lukas Bossard, Till Quack, Luc VanGool, CVPR 2011 | QE: 42.3 | - | |
"Contextual Weighting for Vocabulary Tree based Image Retrieval", Xiaoyu Wang, Ming Yang, Timothee Cour, Shenghuo Zhu, Kai Yu, Tony X. Han, ICCV 2011 | 78.0 | 57 | Large vocabulary, then weighting of the entries. Relevant remarks on comparing results. |
"Asymmetric Hamming Embedding", Mihir Jain, Hervé Jégou, Patrick Gros, ACM MM 2011 | 81.9 | - | Asymmetric coding of local descriptors |
"Object Retrieval and Localization with Spatially-constrained Similarity Measure and k-NN Re-ranking", Xiaohui Shen, Zhe Lin, Jonathan Brandt, Shai Avidan, Ying Wu, CVPR 2012 | 76.2 | Shortlist reranking. As Holidays has few results per query, the reranking is not very useful. | |
"Embedding Spatial Context Information into Inverted File for Large-Scale Image Retrieval", Zhen Liu, Houqiang Li, Wengang Zhou, Qi Tian, ACM MM 2012 | 60 | 38 | - |
"Visual Place Recognition with Repetitive Structures", Akihiko Torii, Josef Sivic, Tomas Pajdla, Masatoshi Okutomi, CVPR 2013 | 74.95 | - | - |
"To aggregate or not to aggregate: selective match kernels for image search", Giorgos Tolias, Yannis Avrithis and Hervé Jégou, ICCV 2013 | 88.0 | - | mAP=81.0 with a binary embedding and the standard descriptors from the website |
"Query Adaptive Similarity for Large Scale Object Retrieval", Danfeng Qin, Christian Wengert, Luc van Gool, CVPR 2013 | 84.4 | - | |
"Semantic-aware Co-indexing for Image Retrieval", Shiliang Zhang, Ming Yang, Xiaoyu Wang, Yuanqing Lin, Qi Tian, ICCV 2013 | 80.86 | 63.34 | uses another set of 1.3M distractor images |
"Packing and Padding: Coupled Multi-index for Accurate Image Retrieval", Liang Zheng, Shengjin Wang , Ziqiong Liu, and Qi Tian, CVPR 2014 | 84.0, SP 85.8 | 69 | Combines SIFT with local color descriptor in inverted file |
"Bayes Merging of Multiple Vocabularies for Scalable Image Retrieval" Liang Zheng, Shengjin Wang , Wengang Zhou, and Qi Tian, CVPR 2014 | 81.92 | 40 | The result for 1M images does not include HE |
"Locality in Generic Instance Search from One Example", Ran Tao, Efstratios Gavves, Cees G.M. Snoek, Arnold W.M. Smeulders, CVPR 2014 | 78.7 | Similar to Tolias et al ICCV13 except that they use FV instead of VLAD to aggregate descriptors in a centroid and PQ instead of HE for encoding | |
"Early burst detection for memory-efficient image retrieval" Shi, Avrithis, Jegou, CVPR 2015 | 88.1 | ||
"Query-Adaptive Late Fusion for Image Search and Person Re-identification" Liang Zheng, Shengjin Wang, Lu Tian, Fei He, Ziqiong Liu, and Qi Tian, CVPR 2015 | 88.0 | 75.3 | Mixture of BoW + GIST + RAND + HS + CNN |
"Pairwise Geometric Matching for Large-scale Object Retrieval", Xinchao Li, Martha Larson, Alan Hanjalic, CVPR 2015 | SP 89.2 | SP 85 | With experiments on 10M images |
Global descriptors | |||
"Evaluation of GIST descriptors for web-scale image search" Matthijs Douze, Hervé Jégou, Sandhawalia Harsimrat, Laurent Amsaleg, Cordelia Schmid, CIVR 2009 | 37.6 | With GIST descriptors (960 dim, uncompressed version) | |
"Packing bag-of-features" Hervé Jégou, Matthijs Douze, Cordelia Schmid, ICCV 2009 |
55.4 (bin. BOF) 45.2 (miniBOF) |
38.1 (bin. BOF) 24.4 (miniBOF) | - |
"Aggregating local descriptors into a compact image representation", Hervé Jégou, Matthijs Douze, Cordelia Schmid, Patrick Pérez, CVPR 2010 | 52.6 | 32.1 | With global VLAD descriptor (8192 dim). |
"Combining attributes and Fisher vectors for efficient image retrieval" Matthijs Douze and Arnau Ramisa and Cordelia Schmid, CVPR 2011 | 69.9 | 6755 dim global descriptor, from many channels (BOW, GIST, color, etc.) | |
"Bag-of-colors for improved image search", Christian Wengert, Matthijs Douze, Hervé Jégou, ACM Multimedia, 2011 | LD: 63.8 | A global color descriptor (256 dim) | |
"Large-Scale Image Retrieval with Compressed Fisher Vectors", Florent Perronnin, Yan Liu, Jorge Sánchez, Hervé Poirier, CVPR 2011 | 70 | 64 | Evaluation of Fisher vectors for retrieval. Numbers for Holidays and Holidays + 1M are not for the same method |
"Asymmetric Distances for Binary Embeddings", Albert Gordo, Florent Perronnin, CVPR 2011 | 60.8 | 37 | Not same method for Holidays and Holidays+1M. The later uses 128 bytes / image on the database side. |
"Aggregating local image descriptors into compact codes", Hervé Jégou, Florent Perronnin, Matthijs Douze, Jorge Sánchez, Patrick Pérez, Cordelia Schmid, PAMI 2012 | 68.9 | With Fisher descriptors (262k dim) | |
"Query Specific Fusion for Image Retrieval", Shaoting Zhang, Ming Yang, Timothee Cour, Kai Yu, Dimitris N. Metaxas, ECCV 2012 | QE: 84.64 | 10M vocabulary BOW + GIST + color descriptor | |
"Negative evidences and co-occurrences in image retrieval: the benefit of PCA and whitening" Hervé Jégou, Ondrej Chum, ECCV 2012 | 61.4 | VLAD in 128 dim, with various improvements | |
"Leveraging Category-Level Labels For Instance-Level Image Retrieval", Albert Gordo, José A. Rodríguez-Serrano, Florent Perronnin, Ernest Valveny, CVPR 2012 | 76.8 | 68 | Comparable with Douze&al. CVPR 2011, with cleaner setup and better results. |
"Weakly Supervised Sparse Coding with Geometric Consistency Pooling", Liujuan Cao, Rongrong Ji, Yue Gao, Yi Yang, Qi Tian, CVPR 2012 | LD: 79 | LD: 62 | Presume learnt on dataset |
"All about VLAD", Relja Arandjelovic, Andrew Zisserman, CVPR 2013 | 64.6 | - | More figure in the paper with different tradeoffs |
"Visual Reranking through Weakly Supervised Multi-Graph Learning", Cheng Deng, Rongrong Ji, Wei Liu, Dacheng Tao, Xinbo Gao, ICCV 2013 | QE: 84.7 | QE: 79.4 | Obtained with very low-dimensional features (BoF + GIST + HSV) total < 4000 D (?) |
"Multi-scale Orderless Pooling of Deep Convolutional Activation Features", Y. Gong, L. Wang, R. Guo, and S. Lazebnik, ECCV 2014 | 80.18 | With low-dimensional CNN-based features (2048 D) | |
"Triangulation embedding and democratic aggregation for image search" Jegou, Zisserman, CVPR 2014 | 77.1 | in 8064D mAP=72 when reduced to 1024D | |
"Exemplar SVMs as Visual Feature Encoders" Joaquin Zepeda and Patrick Perez, CVPR 2015 | 78.3 | 71 | |
"FAemb: a function approximation-based embedding method for image retrieval" Thanh-Toan Do, Quang D. Tran, Ngai-Man Cheung, CVPR 2015 | 75.8 | ||
"Fisher Vectors Meet Neural Networks: A Hybrid Classification Architecture" Florent Perronnin and Diane Larlus, CVPR 2015 | 84.7 | in 4096D Lower levels: SIFT + FV then fully-connected network | |
"Sparse Composite Quantization", Ting Zhang, Guo-Jun Qi, Jinhui Tang, Jingdong Wan, CVPR 2015 | 64.4 | Ultra-compact image descriptors (128 bits) | |
Uses dataset, but does not report results | |||
"Transform Coding for Fast Approximate Nearest Neighbor Search in High Dimensions", Jonathan Brandt, CVPR 2010 | Uses SIFT descriptors from Holidays for NN search | ||
"Robust Fusion: Extreme Value Theory for Recognition Score Normalization" W. Scheirer, A. Rocha, R. Micheals, and T. Boult, ECCV 2010 | Only reports improvements over a baseline algorithm | ||
"Reconstructing an image from its local descriptors" Philippe Weinzaepfel, Herve Jegou, Patrick Perez, CVPR 2011 | Not at all about image retrieval (but still interesting!) | ||
"Collaborative Hashing", Xianglong Liu, Junfeng He, Cheng Deng, Bo Lang, CVPR 2014 | Only descriptors used | ||
"Metric imitation by manifold transfer for efficient vision applications" Dengxin Dai, Till Kroeger, Radu Timofte, Luc Van Gool CVPR 15 | Metric learning. Reports results on 1/2 the dataset (other half used for training) |