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Hanqing Jiang's Projects

2d-3d-semantics icon 2d-3d-semantics

The data skeleton from Joint 2D-3D-Semantic Data for Indoor Scene Understanding

3dr-dataset icon 3dr-dataset

A public dataset for evaluation of 3D Reconstruction

4dgaussians icon 4dgaussians

[CVPR 2024] 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering

animatablegaussians icon animatablegaussians

Code of [CVPR 2024] "Animatable Gaussians: Learning Pose-dependent Gaussian Maps for High-fidelity Human Avatar Modeling"

aniportraitgan icon aniportraitgan

This is a pytorch implementation of the following paper: AniPortraitGAN: Animatable 3D Portrait Generation from 2D Image Collections, SIGGRAPH Asia 2023.

anyloc icon anyloc

AnyLoc: Universal Visual Place Recognition (RA-L 2023)

applealc icon applealc

Native macOS HD audio for not officially supported codecs

awesome-3d-gaussian-splatting icon awesome-3d-gaussian-splatting

Curated list of papers and resources focused on 3D Gaussian Splatting, intended to keep pace with the anticipated surge of research in the coming months.

awesome-rnn icon awesome-rnn

Recurrent Neural Network - A curated list of resources dedicated to RNN

began icon began

Boundary Equibilibrium Generative Adversarial Networks Implementation in Tensorflow

bfm_to_flame icon bfm_to_flame

Convert from Basel Face Model (BFM) to the FLAME head model

boost icon boost

Super-project for modularized Boost

brew icon brew

🍺 The missing package manager for macOS

caffe icon caffe

Caffe: a fast open framework for deep learning.

camodocal icon camodocal

CamOdoCal: Automatic Intrinsic and Extrinsic Calibration of a Rig with Multiple Generic Cameras and Odometry

ccv icon ccv

C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library

cgal icon cgal

The public CGAL repository, see the README below

clip icon clip

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

cmvs-pmvs icon cmvs-pmvs

This software (CMVS) takes the output of a structure-from-motion (SfM) software as input, then decomposes the input images into a set of image clusters of managable size. An MVS software can be used to process each cluster independently and in parallel, where the union of reconstructions from all the clusters should not miss any details that can be otherwise obtained from the whole image set. CMVS should be used in conjunction with an SfM software Bundler and an MVS software PMVS2 (PMVS version 2).

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