English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We present a novel end-to-end method for long-form video temporal groundingto locate specific moments described by natural language queries. Priorlong-video methods for this task typically contain two stages: proposalselection and grounding regression. However, the proposal selection of thesemethods is disjoint from the grounding network and is not trained end-to-end,which limits the effectiveness of these methods. Moreover, these methodsoperate uniformly over the entire temporal window, which is suboptimal givenredundant and irrelevant features in long videos. In contrast to these priorapproaches, we introduce RGNet, a unified network designed for jointlyselecting proposals from hour-long videos and locating moments specified bynatural language queries within them. To achieve this, we redefine proposalselection as a video-text retrieval task, i.e., retrieving the correctcandidate videos given a text query. The core component of RGNet is a unifiedcross-modal RG-Encoder that bridges the two stages with shared features andmutual optimization. The encoder strategically focuses on relevant time framesusing a sparse sampling technique. RGNet outperforms previous methods,demonstrating state-of-the-art performance on long video temporal groundingdatasets MAD and Ego4D. The code is released athttps://github.com/Tanveer81/RGNet

RGNet: A Unified Retrieval and Grounding Network for Long Videos