Usually, learning spatial priors relies on training a structured output model. In this paper, two special cases of discriminative structured output model, i.e. ...

Usually, learning spatial priors relies on training a structured output model. In this paper, two special cases of discriminative structured output model, i.e. ...

Existing approaches to indoor scene understanding for- mulate the problem as a structured prediction task focusing on estimating the 3D bounding box which best ...

Feb 7, 2023 · Abstract. This position paper argues for the use of structured generative models (SGMs) for scene un- derstanding.

PDF | Existing approaches to indoor scene understanding formulate the problem as a structured prediction task focusing on estimating the 3D bounding box.

Existing approaches to indoor scene understanding for- mulate the problem as a structured prediction task focusing on estimating the 3D bounding box which ...

Apr 1, 2013 · We address the problem of understanding an indoor scene from a single image in terms of recovering the room geometry (floor, ceiling, ...

This shows that our designed regional-feature-enhanced structure and dual spatial-aware discriminative loss are effective. In order to further prove the ...

We discuss unsupervised domain adaptation methods for image classification and pixel-level structured prediction tasks, and works on learning disentangled ...

Qualitative evaluations show that MTMamba captures discriminative features and generates precise predictions. Report issue for preceding element. 2 Related ...