luvision (THU-luvision)

THU-luvision

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Company:Tsinghua University

Location:Beijing

Home Page:http://www.luvision.net/

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luvision's repositories

XScale-NVS

The official implementation of the CVPR'24 paper titled "XScale-NVS: Cross-Scale Novel View Synthesis with Hash Featurized Manifold".

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OmniSeg3D

Segment Everything All at Once

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INS-Conv

INS-Conv: Incremental Sparse Convolution for Online 3D Segmentation (CVPR 2022)

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BuildingFusion

This is the official code repository for BuildingFusion, a semantic-aware structural building-scale reconstruction system, which allows collaborative building-scale dense reconstruction, with online semantic and structural understanding. It is able to handle large scale scenes (~1000m^2).

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TextureFusion

This is official repository for Project for Real-Time Globally Consistent Dense 3D Reconstruction With Online Texturing.

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OccuSeg

This is the official code repository for OccuSeg, a state-of-the-art method for accurate joint 3D semantic and instance segmentation.

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SurRF

The official implementation for the paper: SurRF: Unsupervised Multi-view Stereopsis by Learning Surface Radiance Field

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SPECAT

Official Implementation of the CVPR'24 paper: SPECAT: SPatial-spEctral Cumulative-Attention Transformer for High-Resolution Hyperspectral Image Reconstruction

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GIFNet

Source code and dataset for paper 'Group interaction field for learning and explaining pedestrian anticipation'

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GigaMVS

This repository is used for discussing issues regarding the **GigaMVS** dataset and benchmark. Please visit the following website for more details: http://gigamvs.com/

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MILD

open source code for loop closure detection, binary feature based.

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SurfaceNetPlus

This is the official code repository for SurfaceNet+, a volumetric method to handle the ‘incompleteness’ and the ‘inaccuracy’ problems induced by a very sparse MVS setup.

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DeepCAD

DeepCAD: Deep self-supervised learning for calcium imaging denoising

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STPC

SpatioTemporal Photonic Computing

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SurfaceNet

2017 ICCV, SurfaceNet: An End-to-end 3D Neural Network for Multiview Stereopsis

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