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/

Zendy Plus

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

Zendy Tools

Zendy Open

Generating dynamic 3D object from a single-view video is challenging due tothe lack of 4D labeled data. An intuitive approach is to extend previousimage-to-3D pipelines by transferring off-the-shelf image generation modelssuch as score distillation sampling.However, this approach would be slow andexpensive to scale due to the need for back-propagating the information-limitedsupervision signals through a large pretrained model. To address this, wepropose an efficient video-to-4D object generation framework calledEfficient4D. It generates high-quality spacetime-consistent images underdifferent camera views, and then uses them as labeled data to directlyreconstruct the 4D content through a 4D Gaussian splatting model. Importantly,our method can achieve real-time rendering under continuous cameratrajectories. To enable robust reconstruction under sparse views, we introduceinconsistency-aware confidence-weighted loss design, along with a lightlyweighted score distillation loss. Extensive experiments on both synthetic andreal videos show that Efficient4D offers a remarkable 10-fold increase in speedwhen compared to prior art alternatives while preserving the quality of novelview synthesis. For example, Efficient4D takes only 10 minutes to model adynamic object, vs 120 minutes by the previous art model Consistent4D.

Efficient4D: Fast Dynamic 3D Object Generation from a Single-view Video