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cs.CV2021

Nutrition5k: Towards Automatic Nutritional Understanding of Generic Food

Quin Thames, Arjun Karpur, Wade Norris +4

Understanding the nutritional content of food from visual data is a challenging computer vision problem, with the potential to have a positive and widespread impact on public healt…

cs.CV2020

Google Landmarks Dataset v2 -- A Large-Scale Benchmark for Instance-Level Recognition and Retrieval

Tobias Weyand, Andre Araujo, Bingyi Cao +1

While image retrieval and instance recognition techniques are progressing rapidly, there is a need for challenging datasets to accurately measure their performance -- while posing…

cs.CV2020

Unifying Deep Local and Global Features for Image Search

Bingyi Cao, Andre Araujo, Jack Sim

Image retrieval is the problem of searching an image database for items that are similar to a query image. To address this task, two main types of image representations have been s…

cs.CV2018

Detect-to-Retrieve: Efficient Regional Aggregation for Image Search

Marvin Teichmann, Andre Araujo, Menglong Zhu +1

Retrieving object instances among cluttered scenes efficiently requires compact yet comprehensive regional image representations. Intuitively, object semantics can help build the i…

cs.CV2018

CPlaNet: Enhancing Image Geolocalization by Combinatorial Partitioning of Maps

Paul Hongsuck Seo, Tobias Weyand, Jack Sim +1

Image geolocalization is the task of identifying the location depicted in a photo based only on its visual information. This task is inherently challenging since many photos have o…