Content-based image retrieval: approaches and trends of the new age
By Ritendra Datta, Jia Li, James Ze Wang. Multimedia Information Retrieval, 2005
554 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/24b0d89b1df469be8aa12fb797081be87251727a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Dacheng Tao
- Trevor Darrell
- Xiaogang Wang
- Jitendra Malik
- Andrew Zisserman
- Li Fei-Fei
- Yi Yang
Citations in the corpus
- Every Picture Tells a Story: Generating Sentences from Images (2010, unknown): “Since then, a wide range of models has been deployed (reviews in [4,5]); the current best performer is a form of nearest neighbours matching [6].”
- Features for image retrieval: an experimental comparison (2008, methodology): “Two recent reviews of CBIR techniques are given in [15,16].”
- Human Curation and Convnets: Powering Item-to-Item Recommendations on Pinterest (2015, background): “As one of the most popular features on Pinterest 1 , Related Pins is a recommendation system that combines collaborative filtering [19] with content-based [6] retrieval.”
- PatternNet: A Benchmark Dataset for Performance Evaluation of Remote Sensing Image Retrieval (2017, methodology): “…resulted in the significant challenge of how to efficiently manage the large data collections, particularly so that the data of interest can be accessed quickly Content based image retrieval (CBIR) is a useful technique for the fast retrieval of images of interest from a large-scale dataset [1–4].”
- FaceTracer: A Search Engine for Large Collections of Images with Faces (2008, background): “[13] for a recent survey of this field.”
- Describable Visual Attributes for Face Verification and Image Search (2011, unknown): “Early work in appearance-based face verification [29], [57] looked at the L 2 distance between pairs of images in a lower-dimensional subspace obtained using Principal Components Analysis (PCA).”
- Sketch-based 3D model retrieval using diffusion tensor fields of suggestive contours (2010, methodology): “To compute the similarity between a 3D model and a usersketch image, the model is usually projected and rendered from several viewpoints and the best-matching similarity between the sketch image and the projected images are computed.”