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Reconstructing detailed 3D scenes from single-view images remains a challenging task due to limitations in existing approaches, which primarily focus on geometric shape recovery, overlooking object appearances and fine shape details. To…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 Yixin Chen , Junfeng Ni , Nan Jiang , Yaowei Zhang , Yixin Zhu , Siyuan Huang

We present a novel learning-based approach for computing correspondences between non-rigid 3D shapes. Unlike previous methods that either require extensive training data or operate on handcrafted input descriptors and thus generalize poorly…

Machine Learning · Statistics 2020-04-01 Nicolas Donati , Abhishek Sharma , Maks Ovsjanikov

Structured representations such as scene graphs serve as an efficient and compact representation that can be used for downstream rendering or retrieval tasks. However, existing efforts to generate realistic images from scene graphs perform…

Computer Vision and Pattern Recognition · Computer Science 2019-04-23 Subarna Tripathi , Sharath Nittur Sridhar , Sairam Sundaresan , Hanlin Tang

We present a novel inverse rendering-based framework to estimate the 3D shape (per-pixel surface normals and depth) of objects and scenes from single-view polarization images, the problem popularly known as Shape from Polarization (SfP).…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Ashish Tiwari , Shanmuganathan Raman

We propose a system that learns to detect objects and infer their 3D poses in RGB-D images. Many existing systems can identify objects and infer 3D poses, but they heavily rely on human labels and 3D annotations. The challenge here is to…

Computer Vision and Pattern Recognition · Computer Science 2020-11-02 Mihir Prabhudesai , Shamit Lal , Hsiao-Yu Fish Tung , Adam W. Harley , Shubhankar Potdar , Katerina Fragkiadaki

Object compositing based on 2D images is a challenging problem since it typically involves multiple processing stages such as color harmonization, geometry correction and shadow generation to generate realistic results. Furthermore,…

Computer Vision and Pattern Recognition · Computer Science 2022-12-06 Yizhi Song , Zhifei Zhang , Zhe Lin , Scott Cohen , Brian Price , Jianming Zhang , Soo Ye Kim , Daniel Aliaga

Methods for 3D reconstruction such as Photometric stereo recover the shape and reflectance properties using multiple images of an object taken with variable lighting conditions from a fixed viewpoint. Photometric stereo assumes that a scene…

Computer Vision and Pattern Recognition · Computer Science 2018-11-07 Anish R. Khadka , Paolo Remagnino , Vasileios Argyriou

Sparse representation of 3D images is considered within the context of data reduction. The goal is to produce high quality approximations of 3D images using fewer elementary components than the number of intensity points in the 3D array.…

Image and Video Processing · Electrical Eng. & Systems 2019-06-12 Laura Rebollo-Neira , Daniel Whitehouse

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

Reflectometry is a technique that uses the light reflected by a sample to determine properties of the sample. Interferometric reflectometry uses interference between two beams, one of which is incident on ---and reflected back by--- a…

Optics · Physics 2019-10-10 Alexander Nahmad-Rohen , Wolfgang Langbein

Image compositing plays a vital role in photo editing. After inserting a foreground object into another background image, the composite image may look unnatural and inharmonious. When the foreground is photorealistic and the background is…

Computer Vision and Pattern Recognition · Computer Science 2023-11-16 Xudong Wang , Li Niu , Junyan Cao , Yan Hong , Liqing Zhang

We propose an end-to-end inverse rendering pipeline called SupeRVol that allows us to recover 3D shape and material parameters from a set of color images in a super-resolution manner. To this end, we represent both the bidirectional…

Computer Vision and Pattern Recognition · Computer Science 2023-03-17 Mohammed Brahimi , Bjoern Haefner , Tarun Yenamandra , Bastian Goldluecke , Daniel Cremers

We present a mathematical and algorithmic scheme for learning the principal geometric elements in an image or 3D object. We build on recent work that convexifies the basic problem of finding a combination of a small number shapes that…

Computer Vision and Pattern Recognition · Computer Science 2016-07-05 Alireza Aghasi , Justin Romberg

Inferring 3D structure of a generic object from a 2D image is a long-standing objective of computer vision. Conventional approaches either learn completely from CAD-generated synthetic data, which have difficulty in inference from real…

Computer Vision and Pattern Recognition · Computer Science 2021-04-05 Feng Liu , Luan Tran , Xiaoming Liu

Existing online 3D shape repositories contain thousands of 3D models but lack photorealistic appearance. We present an approach to automatically assign high-quality, realistic appearance models to large scale 3D shape collections. The key…

Graphics · Computer Science 2018-09-27 Keunhong Park , Konstantinos Rematas , Ali Farhadi , Steven M. Seitz

The goal of this paper is to take a single 2D image of a scene and recover the 3D structure in terms of a small set of factors: a layout representing the enclosing surfaces as well as a set of objects represented in terms of shape and pose.…

Computer Vision and Pattern Recognition · Computer Science 2018-04-25 Shubham Tulsiani , Saurabh Gupta , David Fouhey , Alexei A. Efros , Jitendra Malik

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

Inverse-designed Silicon photonic metastructures offer an efficient platform to perform analog computations with electromagnetic waves. However, due to computational difficulties, scaling up these metastructures to handle a large number of…

Imaging systems are inherently prone to aberrations. We present an optimization method to design two-dimensional freeform reflectors that minimize aberrations for various parallel ray beams incident on the optical system. We iteratively…

We present implicit displacement fields, a novel representation for detailed 3D geometry. Inspired by a classic surface deformation technique, displacement mapping, our method represents a complex surface as a smooth base surface plus a…

Computer Vision and Pattern Recognition · Computer Science 2022-02-03 Wang Yifan , Lukas Rahmann , Olga Sorkine-Hornung
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