ABSTRACT
Face benchmarks empower the research community to train and evaluate high-performance face recognition systems. In this paper, we contribute a new million-scale recognition benchmark, containing uncurated 4M identities/260M faces (WebFace260M) and cleaned 2M identities/42M faces (WebFace42M) training data, as well as an elaborately designed time-constrained evaluation protocol. Firstly, we collect 4M name lists and download 260M faces from the Internet. Then, a Cleaning Automatically utilizing Self-Training (CAST) pipeline is devised to purify the tremendous WebFace260M, which is efficient and scalable. To the best of our knowledge, the cleaned WebFace42M is the largest public face recognition training set and we expect to close the data gap between academia and industry. Referring to practical deployments, Face Recognition Under Inference Time conStraint (FRUITS) protocol and a new test set with rich attributes are constructed. Besides, we gather a large-scale masked face sub-set for biometrics assessment under COVID-19. For a comprehensive evaluation of face matchers, three recognition tasks are performed under standard, masked and unbiased settings, respectively. Equipped with this benchmark, we delve into million-scale face recognition problems. A distributed framework is developed to train face recognition models efficiently without tampering with the performance. Enabled by WebFace42M, we reduce 40% failure rate on the challenging IJB-C set and rank 3rd among 430 entries on NIST-FRVT. Even 10% data (WebFace4M) shows superior performance compared with the public training sets. Furthermore, comprehensive baselines are established under the FRUITS-100/500/1000 milliseconds protocols. The proposed benchmark shows enormous potential on standard, masked and unbiased face recognition scenarios. Our WebFace260M website is https://www.face-benchmark.org.
Subject(s)
COVID-19ABSTRACT
Recently, kimchi has been recognized as a healthy food worldwide, prompting increased interest in its health benefits and quality characteristics. Although commercial kimchi is manufactured in various countries, little is known about quality differences between the kimchi from different countries. To clarify differences in quality characteristics, minerals, free sugars, organic acids, free amino acids, and volatile compounds, commercial kimchi manufactured in Korea, China, and the United States were investigated. The composition of the microbial community and antioxidant activity were compared. Mineral and free sugar contents were high in Korean commercial kimchi, while the organic acid content was relatively low. The free amino acid content was markedly higher in Korean kimchi than that in kimchi manufactured in China and the United States. In addition, the volatile compound content differed between the kimchi produced in different countries. Considering the microbial communities, Leuconostoc and Weissella were more abundant in commercial kimchi from Korea than that from China or the United States. Commercial kimchi in Korea showed the highest antioxidant activity. These results support the high quality and antioxidant activity of commercial kimchi manufactured in Korea, emphasizing its importance in the global kimchi industry.
ABSTRACT
According to WHO statistics, there are more than 204,617,027 confirmed COVID-19 cases including 4,323,247 deaths worldwide till August 12, 2021. During the coronavirus epidemic, almost everyone wears a facial mask. Traditionally, face recognition approaches process mostly non-occluded faces, which include primary facial features such as the eyes, nose, and mouth. Removing the mask for authentication in airports or laboratories will increase the risk of virus infection, posing a huge challenge to current face recognition systems. Due to the sudden outbreak of the epidemic, there are yet no publicly available real-world masked face recognition (MFR) benchmark. To cope with the above-mentioned issue, we organize the Face Bio-metrics under COVID Workshop and Masked Face Recognition Challenge in ICCV 2021. Enabled by the ultra-large-scale WebFace260M benchmark and the Face Recognition Under Inference Time conStraint (FRUITS) protocol, this challenge (WebFace260M Track) aims to push the frontiers of practical MFR. Since public evaluation sets are mostly saturated or contain noise, a new test set is gathered consisting of elaborated 2,478 celebrities and 60,926 faces. Meanwhile, we collect the world-largest real-world masked test set. In the first phase of WebFace260M Track, 69 teams (total 833 solutions) participate in the challenge and 49 teams exceed the performance of our baseline. There are second phase of the challenge till October 1, 2021 and on-going leaderboard. We will actively update this report in the future.
Subject(s)
COVID-19 , Tumor Virus InfectionsABSTRACT
Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARSCoV- 2) has become a global pandemic and led to a serious impact on public health and economic development. This paper summarizes the source of the first isolated and identified SARS-CoV-2 samples and the problems present in the etiology detection of virus RNA. The necessity and limitation of bronchoscopy use in the diagnosis of COVID-19 were discussed and the occupation protection measures for bronchoscopy in COVID-19 were emphasized. It is important to accelerate the development of new disposable protective devices for the bronchoscopic examination..