Search Results for author: Qi Shan

Found 10 papers, 4 papers with code

MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions

no code implementations27 Apr 2021 Zhenpei Yang, Zhile Ren, Qi Shan, QiXing Huang

Deep learning has made significant impacts on multi-view stereo systems.

RetrievalFuse: Neural 3D Scene Reconstruction with a Database

no code implementations ICCV 2021 Yawar Siddiqui, Justus Thies, Fangchang Ma, Qi Shan, Matthias Nießner, Angela Dai

3D reconstruction of large scenes is a challenging problem due to the high-complexity nature of the solution space, in particular for generative neural networks.

3D Reconstruction 3D Scene Reconstruction +3

Equivariant Neural Rendering

1 code implementation ICML 2020 Emilien Dupont, Miguel Angel Bautista, Alex Colburn, Aditya Sankar, Carlos Guestrin, Josh Susskind, Qi Shan

We propose a framework for learning neural scene representations directly from images, without 3D supervision.

Neural Rendering

LayoutNet: Reconstructing the 3D Room Layout from a Single RGB Image

2 code implementations CVPR 2018 Chuhang Zou, Alex Colburn, Qi Shan, Derek Hoiem

We propose an algorithm to predict room layout from a single image that generalizes across panoramas and perspective images, cuboid layouts and more general layouts (e. g. L-shape room).

3D Room Layouts From A Single RGB Panorama Translation

RIDI: Robust IMU Double Integration

1 code implementation ECCV 2018 Hang Yan, Qi Shan, Yasutaka Furukawa

This paper proposes a novel data-driven approach for inertial navigation, which learns to estimate trajectories of natural human motions just from an inertial measurement unit (IMU) in every smartphone.

Panoramic Structure from Motion via Geometric Relationship Detection

no code implementations5 Dec 2016 Satoshi Ikehata, Ivaylo Boyadzhiev, Qi Shan, Yasutaka Furukawa

This paper addresses the problem of Structure from Motion (SfM) for indoor panoramic image streams, extremely challenging even for the state-of-the-art due to the lack of textures and minimal parallax.

Structure from Motion

IM2CAD

no code implementations CVPR 2017 Hamid Izadinia, Qi Shan, Steven M. Seitz

Given a single photo of a room and a large database of furniture CAD models, our goal is to reconstruct a scene that is as similar as possible to the scene depicted in the photograph, and composed of objects drawn from the database.

Scene Understanding

Occluding Contours for Multi-View Stereo

no code implementations CVPR 2014 Qi Shan, Brian Curless, Yasutaka Furukawa, Carlos Hernandez, Steven M. Seitz

The proposed approach outperforms state of the art MVS techniques for challenging Internet datasets, yielding dramatic quality improvements both around object contours and in surface detail.

Surface Reconstruction

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