9.8k citations · 10.3k across the 10 of their papers we have counts for
10 papers
VideoGLUE: Video General Understanding Evaluation of Foundation Models
Liangzhe Yuan, Nitesh Bharadwaj Gundavarapu, Long Zhao +14
We evaluate the video understanding capabilities of existing foundation models (FMs) using a carefully designed experiment protocol consisting of three hallmark tasks (action recog…
Improving Fairness in Large-Scale Object Recognition by CrowdSourced Demographic Information
Zu Kim, André Araujo, Bingyi Cao +5
There has been increasing awareness of ethical issues in machine learning, and fairness has become an important research topic. Most fairness efforts in computer vision have been f…
Towards A Fairer Landmark Recognition Dataset
Zu Kim, André Araujo, Bingyi Cao +5
We introduce a new landmark recognition dataset, which is created with a focus on fair worldwide representation. While previous work proposes to collect as many images as possible…
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…
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…
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…
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard, Menglong Zhu, Bo Chen +5
We present a class of efficient models called MobileNets for mobile and embedded vision applications. MobileNets are based on a streamlined architecture that uses depth-wise separa…
Large-Scale Image Retrieval with Attentive Deep Local Features
Hyeonwoo Noh, Andre Araujo, Jack Sim +2
We propose an attentive local feature descriptor suitable for large-scale image retrieval, referred to as DELF (DEep Local Feature). The new feature is based on convolutional neura…
PlaNet - Photo Geolocation with Convolutional Neural Networks
Tobias Weyand, Ilya Kostrikov, James Philbin
Is it possible to build a system to determine the location where a photo was taken using just its pixels? In general, the problem seems exceptionally difficult: it is trivial to co…
Visual Landmark Recognition from Internet Photo Collections: A Large-Scale Evaluation
Tobias Weyand, Bastian Leibe
The task of a visual landmark recognition system is to identify photographed buildings or objects in query photos and to provide the user with relevant information on them. With th…