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 study 3D shape modeling from a single image and make contributions to itin three aspects. First, we present Pix3D, a large-scale benchmark of diverseimage-shape pairs with pixel-level 2D-3D alignment. Pix3D has wide applicationsin shape-related tasks including reconstruction, retrieval, viewpointestimation, etc. Building such a large-scale dataset, however, is highlychallenging; existing datasets either contain only synthetic data, or lackprecise alignment between 2D images and 3D shapes, or only have a small numberof images. Second, we calibrate the evaluation criteria for 3D shapereconstruction through behavioral studies, and use them to objectively andsystematically benchmark cutting-edge reconstruction algorithms on Pix3D.Third, we design a novel model that simultaneously performs 3D reconstructionand pose estimation; our multi-task learning approach achieves state-of-the-artperformance on both tasks.

Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling