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The goal of this paper is to learn dense 3D shape correspondence for topology-varying objects in an unsupervised manner. Conventional implicit functions estimate the occupancy of a 3D point given a shape latent code. Instead, our novel…

Computer Vision and Pattern Recognition · Computer Science 2020-10-27 Feng Liu , Xiaoming Liu

We present a learning-based method for interpolating and manipulating 3D shapes represented as point clouds, that is explicitly designed to preserve intrinsic shape properties. Our approach is based on constructing a dual encoding space…

Computer Vision and Pattern Recognition · Computer Science 2021-05-07 Marie-Julie Rakotosaona , Maks Ovsjanikov

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

The objective of this paper is to learn dense 3D shape correspondence for topology-varying generic objects in an unsupervised manner. Conventional implicit functions estimate the occupancy of a 3D point given a shape latent code. Instead,…

Computer Vision and Pattern Recognition · Computer Science 2023-01-02 Feng Liu , Xiaoming Liu

Generating realistic intermediate shapes between non-rigidly deformed shapes is a challenging task in computer vision, especially with unstructured data (e.g., point clouds) where temporal consistency across frames is lacking, and…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Lu Sang , Zehranaz Canfes , Dongliang Cao , Riccardo Marin , Florian Bernard , Daniel Cremers

In order to generate novel 3D shapes with machine learning, one must allow for interpolation. The typical approach for incorporating this creative process is to interpolate in a learned latent space so as to avoid the problem of generating…

Graphics · Computer Science 2020-01-28 Austin Dill , Songwei Ge , Eunsu Kang , Chun-Liang Li , Barnabas Poczos

Implicit functions provide a fundamental basis to model 3D objects, no matter they are rigid or deformable, in computer graphics and geometric modeling. This paper introduces a new constructive scheme of implicitly-defined 3D objects based…

Graphics · Computer Science 2019-06-18 Adriano N. Raposo , Abel J. P. Gomes

Although 3D shape matching and interpolation are highly interrelated, they are often studied separately and applied sequentially to relate different 3D shapes, thus resulting in sub-optimal performance. In this work we present a unified…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Dongliang Cao , Marvin Eisenberger , Nafie El Amrani , Daniel Cremers , Florian Bernard

In this paper, we present a novel implicit glyph shape representation, which models glyphs as shape primitives enclosed by quadratic curves, and naturally enables generating glyph images at arbitrary high resolutions. Experiments on font…

Computer Vision and Pattern Recognition · Computer Science 2021-06-17 Ying-Tian Liu , Yuan-Chen Guo , Yi-Xiao Li , Chen Wang , Song-Hai Zhang

Deep implicit functions (DIFs), as a kind of 3D shape representation, are becoming more and more popular in the 3D vision community due to their compactness and strong representation power. However, unlike polygon mesh-based templates, it…

Computer Vision and Pattern Recognition · Computer Science 2021-05-14 Zerong Zheng , Tao Yu , Qionghai Dai , Yebin Liu

In recent years, neural implicit representations have made remarkable progress in modeling of 3D shapes with arbitrary topology. In this work, we address two key limitations of such representations, in failing to capture local 3D geometric…

Computer Vision and Pattern Recognition · Computer Science 2022-04-01 Yunlu Chen , Basura Fernando , Hakan Bilen , Matthias Nießner , Efstratios Gavves

Neural implicit fields are quickly emerging as an attractive representation for learning based techniques. However, adopting them for 3D shape modeling and editing is challenging. We introduce a method for $\mathbf{E}$diting…

Graphics · Computer Science 2022-02-03 Amir Hertz , Or Perel , Raja Giryes , Olga Sorkine-Hornung , Daniel Cohen-Or

Recent development of neural implicit function has shown tremendous success on high-quality 3D shape reconstruction. However, most works divide the space into inside and outside of the shape, which limits their representing power to…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Jianglong Ye , Yuntao Chen , Naiyan Wang , Xiaolong Wang

Existing 3D surface representation approaches are unable to accurately classify pixels and their orientation lying on the boundary of an object. Thus resulting in coarse representations which usually require post-processing steps to extract…

Computer Vision and Pattern Recognition · Computer Science 2019-01-23 Mateusz Michalkiewicz , Jhony K. Pontes , Dominic Jack , Mahsa Baktashmotlagh , Anders Eriksson

We propose a novel 3D shape correspondence method based on the iterative alignment of so-called smooth shells. Smooth shells define a series of coarse-to-fine shape approximations designed to work well with multiscale algorithms. The main…

Computer Vision and Pattern Recognition · Computer Science 2019-12-03 Marvin Eisenberger , Zorah Lähner , Daniel Cremers

We present Image Sculpting, a new framework for editing 2D images by incorporating tools from 3D geometry and graphics. This approach differs markedly from existing methods, which are confined to 2D spaces and typically rely on textual…

Graphics · Computer Science 2024-01-04 Jiraphon Yenphraphai , Xichen Pan , Sainan Liu , Daniele Panozzo , Saining Xie

This paper considers the shape formation problem within the 3D hybrid model, where a single agent with a strictly limited viewing range and the computational capacity of a deterministic finite automaton manipulates passive tiles through…

Data Structures and Algorithms · Computer Science 2024-05-15 Kristian Hinnenthal , David Liedtke , Christian Scheideler

While many works focus on 3D reconstruction from images, in this paper, we focus on 3D shape reconstruction and completion from a variety of 3D inputs, which are deficient in some respect: low and high resolution voxels, sparse and dense…

Computer Vision and Pattern Recognition · Computer Science 2020-04-16 Julian Chibane , Thiemo Alldieck , Gerard Pons-Moll

Textured 3D morphing creates smooth and plausible interpolation sequences between two 3D objects, focusing on transitions in both shape and texture. This is important for creative applications like visual effects in filmmaking. Previous…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Songlin Yang , Yushi Lan , Honghua Chen , Xingang Pan

Recent advances in 3D human shape reconstruction from single images have shown impressive results, leveraging on deep networks that model the so-called implicit function to learn the occupancy status of arbitrarily dense 3D points in space.…

Computer Vision and Pattern Recognition · Computer Science 2022-05-10 Nicolas Ugrinovic , Albert Pumarola , Alberto Sanfeliu , Francesc Moreno-Noguer
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