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There are many approaches to weakly-supervised training of networks to segment 2D images. By contrast, existing approaches to segmenting volumetric images rely on full-supervision of a subset of 2D slices of the 3D volume. We propose an…

Computer Vision and Pattern Recognition · Computer Science 2022-06-06 Udaranga Wickramasinghe , Patrick M. Jensen , Mian Shah , Jiancheng Yang , Pascal Fua

Estimating the pose of a camera with respect to a 3D reconstruction or scene representation is a crucial step for many mixed reality and robotics applications. Given the vast amount of available data nowadays, many applications constrain…

Computer Vision and Pattern Recognition · Computer Science 2020-11-30 Marcela Mera-Trujillo , Benjamin Smith , Victor Fragoso

Conventional production workflow of high-precision mesh assets necessitates a cumbersome and laborious process of manual sculpting by specialized 3D artists/modelers. The recent years have witnessed remarkable advances in AI-empowered 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Qijian Zhang , Xiaozheng Jian , Xuan Zhang , Wenping Wang , Junhui Hou

Reconstructing dynamic, time-varying scenes with computed tomography (4D-CT) is a challenging and ill-posed problem common to industrial and medical settings. Existing 4D-CT reconstructions are designed for sparse sampling schemes that…

Image and Video Processing · Electrical Eng. & Systems 2021-04-26 Albert W. Reed , Hyojin Kim , Rushil Anirudh , K. Aditya Mohan , Kyle Champley , Jingu Kang , Suren Jayasuriya

We present an approach to semantic scene analysis using deep convolutional networks. Our approach is based on tangent convolutions - a new construction for convolutional networks on 3D data. In contrast to volumetric approaches, our method…

Computer Vision and Pattern Recognition · Computer Science 2018-07-09 Maxim Tatarchenko , Jaesik Park , Vladlen Koltun , Qian-Yi Zhou

Reconstructing 3D object from a single image (RGB or depth) is a fundamental problem in visual scene understanding and yet remains challenging due to its ill-posed nature and complexity in real-world scenes. To address those challenges, we…

Computer Vision and Pattern Recognition · Computer Science 2021-09-10 Qian He , Desen Zhou , Bo Wan , Xuming He

Describing a scene in terms of primitives -- geometrically simple shapes that offer a parsimonious but accurate abstraction of structure -- is an established and difficult fitting problem. Different scenes require different numbers of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Vaibhav Vavilala , Florian Kluger , Seemandhar Jain , Bodo Rosenhahn , Anand Bhattad , David Forsyth

Superpixel decomposition methods are widely used in computer vision and image processing applications. By grouping homogeneous pixels, the accuracy can be increased and the decrease of the number of elements to process can drastically…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Rémi Giraud , Vinh-Thong Ta , Nicolas Papadakis

Partitioning an image into superpixels based on the similarity of pixels with respect to features such as colour or spatial location can significantly reduce data complexity and improve subsequent image processing tasks. Initial algorithms…

Computer Vision and Pattern Recognition · Computer Science 2022-11-30 Jakob Geusen , Gustav Bredell , Tianfei Zhou , Ender Konukoglu

Motivated by applications in robotics and computer vision, we study problems related to spatial reasoning of a 3D environment using sublevel sets of polynomials. These include: tightly containing a cloud of points (e.g., representing an…

Optimization and Control · Mathematics 2017-03-09 Amir Ali Ahmadi , Georgina Hall , Ameesh Makadia , Vikas Sindhwani

Superpixel segmentation can be used as an intermediary step in many applications, often to improve object delineation and reduce computer workload. However, classical methods do not incorporate information about the desired object.…

Computer Vision and Pattern Recognition · Computer Science 2022-04-08 Felipe Belém , Benjamin Perret , Jean Cousty , Silvio J. F. Guimarães , Alexandre Falcão

The paper describes a novel real-time algorithm for finding 3D geometric primitives (cylinders, cones and spheres) from 3D range data. In its core, it performs a fast model fitting with a model update in constant time (O(1)) for each new…

Computer Vision and Pattern Recognition · Computer Science 2016-03-15 Kristiyan Georgiev , Motaz Al-Hami , Rolf Lakaemper

Generative models can create entirely new images, but they can also partially modify real images in ways that are undetectable to the human eye. In this paper, we address the challenge of automatically detecting such local manipulations.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 Stefan Smeu , Elisabeta Oneata , Dan Oneata

Holistic 3D scene understanding entails estimation of both layout configuration and object geometry in a 3D environment. Recent works have shown advances in 3D scene estimation from various input modalities (e.g., images, 3D scans), by…

Computer Vision and Pattern Recognition · Computer Science 2022-11-28 Yinyu Nie , Angela Dai , Xiaoguang Han , Matthias Nießner

Numerous prior studies predominantly emphasize constructing relation vectors for individual neighborhood points and generating dynamic kernels for each vector and embedding these into high-dimensional spaces to capture implicit local…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Shuofeng Sun , Yongming Rao , Jiwen Lu , Haibin Yan

Any solid object can be decomposed into a collection of convex polytopes (in short, convexes). When a small number of convexes are used, such a decomposition can be thought of as a piece-wise approximation of the geometry. This…

Computer Vision and Pattern Recognition · Computer Science 2020-04-14 Boyang Deng , Kyle Genova , Soroosh Yazdani , Sofien Bouaziz , Geoffrey Hinton , Andrea Tagliasacchi

CAD model retrieval to real-world scene observations has shown strong promise as a basis for 3D perception of objects and a clean, lightweight mesh-based scene representation; however, current approaches to retrieve CAD models to a query…

Computer Vision and Pattern Recognition · Computer Science 2022-03-25 Tim Beyer , Angela Dai

In this paper, we aim to recover the 3D human pose from 2D body joints of a single image. The major challenge in this task is the depth ambiguity since different 3D poses may produce similar 2D poses. Although many recent advances in this…

Computer Vision and Pattern Recognition · Computer Science 2019-06-03 Mengxi Jiang , Zhuliang Yu , Cuihua Li , Yunqi Lei

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

We present a new object representation, called Dense RepPoints, that utilizes a large set of points to describe an object at multiple levels, including both box level and pixel level. Techniques are proposed to efficiently process these…

Computer Vision and Pattern Recognition · Computer Science 2020-05-19 Ze Yang , Yinghao Xu , Han Xue , Zheng Zhang , Raquel Urtasun , Liwei Wang , Stephen Lin , Han Hu