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3D Object Duplicate Detection for Video Retrieval

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Graph Embedding for Retrieval

Chi Thang Duong

Information retrieval (IR) systems such as search engines are important for people to find what they need among the tremendous amount of data available in their organization or on the Internet. These IR systems enable users to search in a large data collec ...

EPFL2022

Knowledge-Aware Cross-Modal Text-Image Retrieval for Remote Sensing Images

Devis Tuia, Christel Marie Tartini-Chappuis, Li Mi, Siran Li

Image-based retrieval in large Earth observation archives is difficult, because one needs to navigate across thousands of candidate matches only with the proposition image as a guide. By using text as a query language, the retrieval system gains in usabili ...

2022

QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval

Shaokai Ye, Yuan He, Hang Su, Jinfeng Li

We study the query-based attack against image retrieval to evaluate its robustness against adversarial examples under the black-box setting, where the adversary only has query access to the top-1 ranked unlabeled images from the database. Compared with que ...

IEEE COMPUTER SOC2021

Deep Feature Factorization For Content-Based Image Retrieval And Localization

Sabine Süsstrunk, Edo Collins

State of the art content-based image retrieval algorithms owe their excellent performance to the rich semantics encoded in the deep activations of a convolutional neural network. The difference between these algorithms lies mostly in how activations are co ...

IEEE2019

Geometric deep learning: going beyond Euclidean data

Pierre Vandergheynst, Michael Bronstein

Many signal processing problems involve data whose underlying structure is non-Euclidean, but may be modeled as a manifold or (combinatorial) graph. For instance, in social networks, the characteristics of users can be modeled as signals on the vertices of ...

2017

Adaptive relevance feedback for large-scale image retrieval

François Fleuret, Nicolae Suditu

Content-based image retrieval aims at substituting traditional indexing based on manual annotation by using automatically-extracted visual indexing features. Novel techniques are needed however to efficiently deal with the semantic gap (i.e. the partial ma ...

2016

Graph Signal Processing

Ntorina Thanou

Over the past few decades we have been experiencing an explosion of information generated by large networks of sensors and other data sources. Much of this data is intrinsically structured, such as traffic evolution in a transportation network, temperature ...

EPFL2016

Geotag Propagation with User Trust Modeling

Touradj Ebrahimi, Jong Seok Lee, Ivan Ivanov, Péter Vajda

The amount of information that people share on social networks is constantly increasing. People also comment, annotate, and tag their own content (videos, photos, notes, etc.), as well as the content of others. In many cases, the content is tagged manually ...

Springer-Verlag2013

Adaptive Relevance Feedback for Large-scale Image Retrieval

Nicolae Suditu

Our research addresses the need for an efficient, effective, and interactive access to large-scale image collections. Image retrieval needs are evolving beyond the capabilities of the traditional indexing based on manual annotation, and the most desirable ...

EPFL2013

Comparative Study of Trust Modeling For Automatic Landmark Tagging

Touradj Ebrahimi, Ivan Ivanov, Péter Vajda

Many images uploaded to social networks are related to travel, since people consider traveling to be an important event in their life. However, a signiﬁcant amount of travel images on the Internet lack proper geographical annotations or tags. In many cases ...

Ieee-Inst Electrical Electronics Engineers Inc2013