Oscar® Spotlight: “Time”

[AzertFurce]

Oscar® Spotlight: “Time” Opinion | Australia is standing up to Facebook and Big Tech. It shouldn’t fight alone.

When it comes to keeping in shape, seniors take exercise where they can find it, and turn their efforts into opportunities for social interaction, too. In 2002, almost one in every five fitness club members was over 55. Today parks, libraries, community colleges, senior centers and national organizations are offering more programs for active retirees than ever before. Although not in everyone's budget, travel is on the wish list of many Baby Boomers and retirees, and may account for up to 80 percent of non-business travel. From learning a new skill like gourmet cooking (in Tuscany), to participating in either domestic or international goodwill projects, seniors who travel can tailor their excursions to fulfill passions like antiquing, museum hopping or just lazing around on the beach. Whether it's a weekend getaway by car (or bicycle) or a cruise around the world, a change of scenery is the brass ring for many who look forward to the time when the week doesn't start with a long commute and a quick cup of coffee before the Monday morning meeting. Baby Boomers represent 28 percent of the U.S. 7 seconds another Baby Boomer turns 50, according to Baby Boomer Magazine. Bakalar, Nicholas. "Retirement Contentment in Reach for Unhappy Men." 4/4/06. (5/16/11).http://www.nytimes.com/2006/04/04/healt ... ogy/04reti. Corporation for National. Craft and Hobby Association. Dowd, Casey. "Volunteer Tourism Appealing for Boomers." Fox Business. Eisold, Ken, Ph.D. "Should You Retire Early?" Psychology Today. Ertel, Karen A. ScD, M. Maria Glymour, ScD, and Lisa F. Berkman, PhD. American Journal of Public Health. Gottlieb, Elaine. "Vacations for Older Adults: Education, Adventure, Service-How About All of the Above?" A Healthy Me. Quilty, Susan. "There's More to Retirement Than Golfing." 55 Places. Williams, Kandy. "Social Activities for Seniors." My Local Health.|As the European Championship approaches, all eyes in Europe are on the host countries, Poland and Ukraine. Of these two nations, Ukraine is by far the least visited and well known. Nevertheless, there is a wealth of beautiful cities located in Ukraine, especially in the western area. At the forefront of Ukraine's magnificence is the city of Lviv, located close to the border with Poland. Lviv has a rich history, having been under the rule of the Polish Empire, Austrian Empire, and Russian Empire, along with having Mongol and Tartar influence dating back to the early years of the last millennium. As a result of this cultural miscegenation, visiting Lviv is similar to visiting a medley of European cities. The grandeur of the old city was so spectacular that the heart of Lviv was proclaimed a UNESCO World Heritage Site, and has been colloquially named the Paris of Eastern Europe.
The core of RC is the interaction between text passage and query. TSGV models the interaction between two different modalities, making it more arduous and challenging. Subsequent solutions focus more on effective and efficient multimodal interactions between video and query. In this survey, we aim to provide a comprehensive and systematic review of TSGV research. We collect papers from reputable conferences and journals in CV, NLP, MM, IR, and machine learning areas, e.g., CVPR, ECCV, ICCV, WACV, BMVC, ACL, EMNLP, NAACL, SIGIR, ACM MM, NeurIPS, AAAI, IJCAI, and TPAMI, TMM, TIP, etc. The papers were mainly published from 2017 to 2021. For paper collection, we primarily rely on academic search engines and digital libraries, such as IEEE Xplore, ACM Digital Library, ScienceDirect, Springer, ACL Anthology, CVF Open Access, etc. We also adopt Google Scholar to collect papers in other conferences/journals, and open-sourced articles.111A number of keywords and their combinations are utilized for paper searching, including moment, grounding, localization, language query, video retrieval, moment retrieval, video grounding, temporal grounding, moment localization, video localization, temporal localization, temporal language grounding, temporal sentence grounding, etc. Fig. 2 summarizes the statistics of the collected papers.
BridgeFormer is able to be removed for downstream retrieval, rendering an efficient and flexible model with only two encoders. Our method outperforms state-of-the-art methods on the popular text-to-video retrieval task in five datasets with different experimental setups (i.e., zero-shot and fine-tune), including HowTo100M (one million videos). We further conduct zero-shot action recognition, which can be cast as video-to-text retrieval, and our approach also significantly surpasses its counterparts. As an additional benefit, our method achieves competitive results with much shorter pre-training videos on single-modality downstream tasks, e.g., action recognition with linear evaluation. Pre-training a model to learn transferable representations for video-text retrieval requires the understanding of video concepts, text semantics, and the relationships between videos and texts. Existing works for video-text pre-training can be divided into two main categories. A new module in vitro, termed BridgeFormer, makes it possible, as illustrated in Fig. 1. Based on the backbone of a “dual-encoder” framework, BridgeFormer is trained to answer the “questions” generated by the text features via visual reasoning with the video features.


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Oscar® Spotlight: “Time”
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Oscar® Spotlight: “Time”
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Oscar® Spotlight: “Time”
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[GregoryZer]

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[GregoryZer]

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[GregoryZer]

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