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We present an efficient and automatic approach for accurate reconstruction of instances of big 3D objects from multiple, unorganized and unstructured point clouds, in presence of dynamic clutter and occlusions. In contrast to conventional…

Computer Vision and Pattern Recognition · Computer Science 2017-08-18 Tolga Birdal , Slobodan Ilic

We introduce a novel camera model for monocular 3D Morphable Model (3DMM) regression methods that effectively captures the perspective distortion effect commonly seen in close-up facial images. Fitting 3D morphable models to video is a key…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Toby Chong , Ryota Nakajima

We present a novel, end-to-end approach to align CAD models to an 3D scan of a scene, enabling transformation of a noisy, incomplete 3D scan to a compact, CAD reconstruction with clean, complete object geometry. Our main contribution lies…

Computer Vision and Pattern Recognition · Computer Science 2019-06-12 Armen Avetisyan , Angela Dai , Matthias Nießner

This paper propose a interactive 3D modeling method and corresponding system based on single or multiple uncalibrated images. The main feature of this method is that, according to the modeling habits of ordinary people, the 3D model of the…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Zhi He , Rui Wang , Wei Hua , Yuchi Huo

The aim of our paper is to render an object in 3-dimension using a set of its orthographic views. Corner detector (Harris Detector) is applied on the input views to obtain control points. These control points are projected perpendicular to…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Sunil Tiwari , Payal Fofadiya , Vicky Vishwakarma

3D reconstruction from single view images is an ill-posed problem. Inferring the hidden regions from self-occluded images is both challenging and ambiguous. We propose a two-pronged approach to address these issues. To better incorporate…

Computer Vision and Pattern Recognition · Computer Science 2019-03-27 Priyanka Mandikal , K L Navaneet , Mayank Agarwal , R. Venkatesh Babu

Humans exhibit an innate capacity to rapidly perceive and segment objects from video observations, and even mentally assemble them into structured 3D scenes. Replicating such capability, termed compositional 3D reconstruction, is pivotal…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Mingyu Dong , Chong Xia , Mingyuan Jia , Weichen Lyu , Long Xu , Zheng Zhu , Yueqi Duan

Computer-aided design (CAD) is crucial in prototyping 3D objects through geometric instructions (i.e., CAD programs). In practical design workflows, designers often engage in time-consuming reviews and refinements of these prototypes by…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Jiali Chen , Xusen Hei , HongFei Liu , Yuancheng Wei , Zikun Deng , Jiayuan Xie , Yi Cai , Li Qing

Learning-based 3D reconstruction has emerged as a transformative technique in autonomous driving, enabling precise modeling of environments through advanced neural representations. It has inspired pioneering solutions for vital tasks in…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Liewen Liao , Weihao Yan , Wang Xu , Ming Yang , Songan Zhang , H. Eric Tseng

The three-dimensional reconstruction of scenes from multiple views has made impressive strides in recent years, chiefly by methods correlating isolated feature points, intensities, or curvilinear structure. In the general setting, i.e.,…

Computer Vision and Pattern Recognition · Computer Science 2017-07-14 Anil Usumezbas , Ricardo Fabbri , Benjamin Kimia

The challenging task of 3D planar reconstruction from images involves several sub-tasks including frame-wise plane detection, segmentation, parameter regression and possibly depth prediction, along with cross-frame plane correspondence and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Jingjia Shi , Shuaifeng Zhi , Kai Xu

Human perception of 3D shapes goes beyond reconstructing them as a set of points or a composition of geometric primitives: we also effortlessly understand higher-level shape structure such as the repetition and reflective symmetry of object…

Computer Vision and Pattern Recognition · Computer Science 2019-08-13 Yonglong Tian , Andrew Luo , Xingyuan Sun , Kevin Ellis , William T. Freeman , Joshua B. Tenenbaum , Jiajun Wu

Creating geometric abstracted models from image-based scene reconstructions is difficult due to noise and irregularities in the reconstructed model. In this paper, we present a geometric modeling method for noisy reconstructions dominated…

Computer Vision and Pattern Recognition · Computer Science 2014-04-22 Thomas Holzmann , Christof Hoppe , Stefan Kluckner , Horst Bischof

Building an online 3D LiDAR mapping system that produces a detailed surface reconstruction while remaining computationally efficient is a challenging task. In this paper, we present PlanarMesh, a novel incremental, mesh-based LiDAR…

Robotics · Computer Science 2025-10-16 Jiahao Wang , Nived Chebrolu , Yifu Tao , Lintong Zhang , Ayoung Kim , Maurice Fallon

We propose a method to efficiently compute tomographic projections of a 3D volume represented by a linear combination of shifted B-splines. To do so, we propose a ray-tracing algorithm that computes 3D line integrals with arbitrary…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Youssef Haouchat , Sepand Kashani , Aleix Boquet-Pujadas , Philippe Thévenaz , Michael Unser

Existing 3D reconstruction methods utilize guidances such as 2D images, 3D point clouds, shape contours and single semantics to recover the 3D surface, which limits the creative exploration of 3D modeling. In this paper, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Liangchen Li , Caoliwen Wang , Yuqi Zhou , Bailin Deng , Juyong Zhang

Conventional methods of 3D object generative modeling learn volumetric predictions using deep networks with 3D convolutional operations, which are direct analogies to classical 2D ones. However, these methods are computationally wasteful in…

Computer Vision and Pattern Recognition · Computer Science 2017-06-22 Chen-Hsuan Lin , Chen Kong , Simon Lucey

We present a novel 3D shape completion method that operates directly on unstructured point clouds, thus avoiding resource-intensive data structures like voxel grids. To this end, we introduce KAPLAN, a 3D point descriptor that aggregates…

Computer Vision and Pattern Recognition · Computer Science 2020-10-19 Audrey Richard , Ian Cherabier , Martin R. Oswald , Marc Pollefeys , Konrad Schindler

Image-guided object assembly represents a burgeoning research topic in computer vision. This paper introduces a novel task: translating multi-view images of a structural 3D model (for example, one constructed with building blocks drawn from…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Hongyu Yan , Yadong Mu

The convergence of generative artificial intelligence and advanced computer vision technologies introduces a groundbreaking approach to transforming textual descriptions into three-dimensional representations. This research proposes a fully…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Venkat Kumar R , Deepak Saravanan