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Related papers: Skeletal Representations and Applications

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As the intermediate-level representations bridging the two levels, structured representations of visual scenes, such as visual relationships between pairwise objects, have been shown to not only benefit compositional models in learning to…

Computer Vision and Pattern Recognition · Computer Science 2022-07-12 Meng-Jiun Chiou

This paper focuses on the challenging problem of 3D pose estimation of a diverse spectrum of articulated objects from single depth images. A novel structured prediction approach is considered, where 3D poses are represented as skeletal…

Computer Vision and Pattern Recognition · Computer Science 2016-12-05 Yu Zhang , Chi Xu , Li Cheng

The recent success of implicit neural scene representations has presented a viable new method for how we capture and store 3D scenes. Unlike conventional 3D representations, such as point clouds, which explicitly store scene properties in…

Computer Vision and Pattern Recognition · Computer Science 2021-01-19 Amit Kohli , Vincent Sitzmann , Gordon Wetzstein

Traditional explicit 3D representations, such as point clouds and meshes, demand significant storage to capture fine geometric details and require complex indexing systems for surface lookups, making functional representations an efficient,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Panagiotis Sapoutzoglou , George Terzakis , Georgios Floros , Maria Pateraki

Neural reconstruction and rendering strategies have demonstrated state-of-the-art performances due, in part, to their ability to preserve high level shape details. Existing approaches, however, either represent objects as implicit surface…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Angtian Wang , Yuanlu Xu , Nikolaos Sarafianos , Robert Maier , Edmond Boyer , Alan Yuille , Tony Tung

Recently, implicit neural representations have gained popularity for learning-based 3D reconstruction. While demonstrating promising results, most implicit approaches are limited to comparably simple geometry of single objects and do not…

Computer Vision and Pattern Recognition · Computer Science 2020-08-04 Songyou Peng , Michael Niemeyer , Lars Mescheder , Marc Pollefeys , Andreas Geiger

This paper focuses on the challenging task of learning 3D object surface reconstructions from RGB images. Existingmethods achieve varying degrees of success by using different surface representations. However, they all have their own…

Computer Vision and Pattern Recognition · Computer Science 2021-06-11 Jiapeng Tang , Xiaoguang Han , Mingkui Tan , Xin Tong , Kui Jia

Articulated objects (e.g., doors and drawers) exist everywhere in our life. Different from rigid objects, articulated objects have higher degrees of freedom and are rich in geometries, semantics, and part functions. Modeling different kinds…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Yushi Du , Ruihai Wu , Yan Shen , Hao Dong

Object skeleton is a useful cue for object detection, complementary to the object contour, as it provides a structural representation to describe the relationship among object parts. While object skeleton extraction in natural images is a…

Computer Vision and Pattern Recognition · Computer Science 2016-04-07 Wei Shen , Kai Zhao , Yuan Jiang , Yan Wang , Zhijiang Zhang , Xiang Bai

The rapid advances in 3D scanning and acquisition techniques have given rise to the explosive increase of volumetric digital models in recent years. This dissertation systematically trailblazes a novel volumetric modeling framework to…

Graphics · Computer Science 2013-08-06 Bo Li

Recent advances in 3D X-ray Computed Tomographic (CT) sensors have stimulated research efforts to unveil the extremely complex micro-scale processes that control the activity of soil microorganisms. Voxel-based description (up to hundreds…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Olivier Monga , Zakaria Belghali , Mouad Klai , Lucie Druoton , Dominique Michelucci , Valerie Pot

Template 3D shapes are useful for many tasks in graphics and vision, including fitting observation data, analyzing shape collections, and transferring shape attributes. Because of the variety of geometry and topology of real-world shapes,…

Computer Vision and Pattern Recognition · Computer Science 2019-04-16 Kyle Genova , Forrester Cole , Daniel Vlasic , Aaron Sarna , William T. Freeman , Thomas Funkhouser

We present a versatile formulation of the convolution operation that we term a "mapped convolution." The standard convolution operation implicitly samples the pixel grid and computes a weighted sum. Our mapped convolution decouples these…

Computer Vision and Pattern Recognition · Computer Science 2019-06-27 Marc Eder , True Price , Thanh Vu , Akash Bapat , Jan-Michael Frahm

The skeleton is an essential shape characteristic providing a compact representation of the studied shape. Its computation on the image grid raises many issues. Due to the effects of discretization, the required properties of the skeleton -…

Computer Vision and Pattern Recognition · Computer Science 2014-06-03 Aurélie Leborgne , Julien Mille , Laure Tougne

One challenge that remains open in 3D deep learning is how to efficiently represent 3D data to feed deep networks. Recent works have relied on volumetric or point cloud representations, but such approaches suffer from a number of issues…

Computer Vision and Pattern Recognition · Computer Science 2019-01-25 Jhony K. Pontes , Chen Kong , Sridha Sridharan , Simon Lucey , Anders Eriksson , Clinton Fookes

Shape priors have long been known to be effective when reconstructing 3D shapes from noisy or incomplete data. When using a deep-learning based shape representation, this often involves learning a latent representation, which can be either…

Computer Vision and Pattern Recognition · Computer Science 2022-06-22 Patrick M. Jensen , Udaranga Wickramasinghe , Anders B. Dahl , Pascal Fua , Vedrana A. Dahl

Recently introduced implicit field representations offer an effective way of generating 3D object shapes. They leverage implicit decoder trained to take a 3D point coordinate concatenated with a shape encoding and to output a value which…

Computer Vision and Pattern Recognition · Computer Science 2021-10-13 Magdalena Proszewska , Marcin Mazur , Tomasz Trzciński , Przemysław Spurek

Skeletal polyhedra are discrete connected structures consisting of finite (planar or skew) or infinite (linear, planar, or spatial) polygons as faces, with two faces on each edge and a circular vertex figure at each vertex. The present…

Combinatorics · Mathematics 2026-02-24 Egon Schulte , Tomas Skacel

Statistical shape modeling (SSM) is an essential tool for analyzing variations in anatomical morphology. In a typical SSM pipeline, 3D anatomical images, gone through segmentation and rigid registration, are represented using…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Hong Xu , Shireen Y. Elhabian

Object recognition has seen significant progress in the image domain, with focus primarily on 2D perception. We propose to leverage existing large-scale datasets of 3D models to understand the underlying 3D structure of objects seen in an…

Computer Vision and Pattern Recognition · Computer Science 2020-07-28 Weicheng Kuo , Anelia Angelova , Tsung-Yi Lin , Angela Dai
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