Source code for 2021 ICCV paper "In-the-Wild Single Camera 3D Reconstruction Through Moving Water Surfaces"

Overview

In-the-Wild Single Camera 3D Reconstruction
Through Moving Water Surfaces

This is the PyTorch implementation for 2021 ICCV paper "In-the-Wild Single Camera 3D Reconstruction Through Moving Water Surfaces"

Project Page | Paper | Supplemental Material

In-the-Wild Single Camera 3D Reconstruction Through Moving Water Surfaces
Jinhui Xiong, Wolfgang Heidrich
KAUST
ICCV 2021 (Oral)

We propose a differentiable framework to estimate underwater scene geometry along with the time-varying water surface. The inputs to our model are a video sequence captured by a fixed camera. Dense correspondence from each frame to a world reference frame (selected from the input sequences) is pre-computed, ensuring the reconstruction is performed in a unified coordinate system. We feed the flow fields, together with initialized water surfaces and scene geometry (all are initialized as planar surfaces), into the framework, which incorporates ray casting, Snell’s law and multi-view triangulation. The gradients of the specially designed losses with respect to water surfaces and scene geometry are back-propagated, and all parameters are simultaneously optimized. The final result is a quality reconstruction of the underwater scene, along with an estimate of the time-varying water-air interface. The data shown here was captured in a public fountain environment.

Prerequisite

The code was tested with python>=3.7 & PyTorch>=1.3 & cuda>=10.0 on Nvidia RTX 2080 Ti
Minor change on the code if there is compatibility issue. It needs around 10 GB GPU memory.

Setup

conda create -n moving_water python=3.7
conda activate moving_water

conda install pytorch torchvision -c pytorch
conda install -c conda-forge opencv scikit-image
conda install -c anaconda scipy

Run the code

Please go to example folder, download the cached coefficient matrices (there are three matrices for each example) and execute:

python3 run.py

Citation

@inproceedings{xiong2021inthewild,
  title={In-the-Wild Single Camera 3D Reconstruction Through Moving Water Surfaces},
  author={Jinhui Xiong and Wolfgang Heidrich},
  year={2021},
  booktitle={ICCV}
}

Contact

Please contact Jinhui Xiong [email protected] if you have any question or comment.

Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"

Hold me tight! Influence of discriminative features on deep network boundaries This is the source code to reproduce the experiments of the NeurIPS 202

EPFL LTS4 19 Dec 10, 2021
Unsupervised Image Generation with Infinite Generative Adversarial Networks

Unsupervised Image Generation with Infinite Generative Adversarial Networks Here is the implementation of MICGANs using DCGAN architecture on MNIST da

16 Dec 24, 2021
Snscrape-jsonl-urls-extractor - Extracts urls from jsonl produced by snscrape

snscrape-jsonl-urls-extractor extracts urls from jsonl produced by snscrape Usag

1 Feb 26, 2022
Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder

RAVE: Realtime Audio Variational autoEncoder Official implementation of RAVE: A variational autoencoder for fast and high-quality neural audio synthes

ACIDS 587 Jan 01, 2023
Pre-trained Deep Learning models and demos (high quality and extremely fast)

OpenVINO™ Toolkit - Open Model Zoo repository This repository includes optimized deep learning models and a set of demos to expedite development of hi

OpenVINO Toolkit 3.4k Dec 31, 2022
Single Image Deraining Using Bilateral Recurrent Network (TIP 2020)

Single Image Deraining Using Bilateral Recurrent Network Introduction Single image deraining has received considerable progress based on deep convolut

23 Aug 10, 2022
The code for the NeurIPS 2021 paper "A Unified View of cGANs with and without Classifiers".

Energy-based Conditional Generative Adversarial Network (ECGAN) This is the code for the NeurIPS 2021 paper "A Unified View of cGANs with and without

sianchen 22 May 28, 2022
Code for the paper "Reinforced Active Learning for Image Segmentation"

Reinforced Active Learning for Image Segmentation (RALIS) Code for the paper Reinforced Active Learning for Image Segmentation Dependencies python 3.6

Arantxa Casanova 79 Dec 19, 2022
QuadTree Attention for Vision Transformers (ICLR2022)

This repository contains codes for quadtree attention. This repo contains codes for feature matching, image classficiation, object detection and seman

tangshitao 222 Dec 28, 2022
Compact Bidirectional Transformer for Image Captioning

Compact Bidirectional Transformer for Image Captioning Requirements Python 3.8 Pytorch 1.6 lmdb h5py tensorboardX Prepare Data Please use git clone --

YE Zhou 19 Dec 12, 2022
Complete system for facial identity system

Complete system for facial identity system. Include one-shot model, database operation, features visualization, monitoring

4 May 02, 2022
Code for reproducing our paper: LMSOC: An Approach for Socially Sensitive Pretraining

LMSOC: An Approach for Socially Sensitive Pretraining Code for reproducing the paper LMSOC: An Approach for Socially Sensitive Pretraining to appear a

Twitter Research 11 Dec 20, 2022
Transfer-Learn is an open-source and well-documented library for Transfer Learning.

Transfer-Learn is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consist

THUML @ Tsinghua University 2.2k Jan 03, 2023
A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks

Simple implementation of Equivariant GNN A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction. Just 50 lines of

Arsenii Senya Ashukha 97 Dec 23, 2022
Unofficial PyTorch Implementation of "DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features"

Pytorch Implementation of Deep Orthogonal Fusion of Local and Global Features (DOLG) This is the unofficial PyTorch Implementation of "DOLG: Single-St

DK 96 Jan 06, 2023
This repository contains the code for: RerrFact model for SciVer shared task

RerrFact This repository contains the code for: RerrFact model for SciVer shared task. Setup for Inference 1. Download SciFact database Download the S

Ashish Rana 1 May 22, 2022
Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices

Face-Mesh Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices. It employs machine learning

Farnam Javadi 9 Dec 21, 2022
Proof of concept GnuCash Webinterface

Proof of Concept GnuCash Webinterface This may one day be a something truly great. Milestones [ ] Browse accounts and view transactions [ ] Record sim

Josh 14 Dec 28, 2022
Baseline for the Spoofing-aware Speaker Verification Challenge 2022

Introduction This repository contains several materials that supplements the Spoofing-Aware Speaker Verification (SASV) Challenge 2022 including: calc

40 Dec 28, 2022
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing

Notice: Support for Python 3.6 will be dropped in v.0.2.1, please plan accordingly! Efficient and Scalable Physics-Informed Deep Learning Collocation-

tensordiffeq 74 Dec 09, 2022