RGBD-Net - This repository contains a pytorch lightning implementation for the 3DV 2021 RGBD-Net paper.

Overview

RGBD-Net

IEEE Paper | arXiv

This repository contains a pytorch lightning implementation for the 3DV 2021 RGBD-Net paper. We propose a new cascaded architecture for novel view synthesis, called RGBD-Net, which consists of two core components: a hierarchical depth regression network and a depth-aware generator network. The former one predicts depth maps of the target views by using adaptive depth scaling, while the latter one leverages the predicted depths and renders spatially and temporally consistent target images.


Pipeline

Installation

Tested on Ubuntu 16.04 + Pytorch 1.8 + Pytorch Lignting 1.3.5

Install environment:

pip install pytorch-lightning, inplace_abn
pip install imageio, pillow, scikit-image, opencv-python, config-argparse, lpips

DTU dataset

Data download

Download the preprocessed DTU training data and Depth_raw from original MVSNet repo and unzip. We provide a DTU example, please follow with the example's folder structure.

Training model

With depth supervision

python train.py --root_dir dataset_path --num_epochs 32 \
                --batch_size 4 --depth_interval 2.65 --n_depths 8 32 48 --interval_ratios 1.0 2.0 4.0 \
                --optimizer adam --lr 1e-3 --lr_scheduler cosine --num_gpus 4 --loss_type sup --exp_name sup \
                --ckpt_dir ./ckpts --log_dir ./logs

Without depth supervision

python train.py --root_dir dataset_path --num_epochs 32 \
                --batch_size 4 --depth_interval 2.65 --n_depths 8 32 48 --interval_ratios 1.0 2.0 4.0 \
                --optimizer adam --lr 1e-3 --lr_scheduler cosine --num_gpus 4 --loss_type unsup --exp_name unsup \
                --ckpt_dir ./ckpts --log_dir ./logs

Testing model

Please change the weight path in test.py to your trained model and execute python test.py

python test.py --root_dir dataset_path

Citation

If you find our code or paper helps, please consider citing:

@inproceedings{nguyen2021rgbd,
  title={RGBD-Net: Predicting color and depth images for novel views synthesis},
  author={Nguyen-Ha, Phong and Karnewar, Animesh and Huynh, Lam and Rahtu, Esa and Heikkila, Janne},
  booktitle={Proceedings of the International Conference on 3D Vision},
  year={2021}
}

Big thanks to CasMVSNet_pl, our code is partially borrowing from them.

Code related to the manuscript "Averting A Crisis In Simulation-Based Inference"

Abstract We present extensive empirical evidence showing that current Bayesian simulation-based inference algorithms are inadequate for the falsificat

Montefiore Artificial Intelligence Research 3 Nov 14, 2022
Official implementation of Deep Burst Super-Resolution

Deep-Burst-SR Official implementation of Deep Burst Super-Resolution Publication: Deep Burst Super-Resolution. Goutam Bhat, Martin Danelljan, Luc Van

Goutam Bhat 113 Dec 19, 2022
Pytorch implementation for "Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion" (NeurIPS 2021)

Density-aware Chamfer Distance This repository contains the official PyTorch implementation of our paper: Density-aware Chamfer Distance as a Comprehe

Tong WU 93 Dec 15, 2022
This repository contains the source codes for the paper AtlasNet V2 - Learning Elementary Structures.

AtlasNet V2 - Learning Elementary Structures This work was build upon Thibault Groueix's AtlasNet and 3D-CODED projects. (you might want to have a loo

Théo Deprelle 123 Nov 11, 2022
Chainer Implementation of Semantic Segmentation using Adversarial Networks

Semantic Segmentation using Adversarial Networks Requirements Chainer (1.23.0) Differences Use of FCN-VGG16 instead of Dilated8 as Segmentor. Caution

Taiki Oyama 99 Jun 28, 2022
Unofficial PyTorch implementation of the Adaptive Convolution architecture for image style transfer

AdaConv Unofficial PyTorch implementation of the Adaptive Convolution architecture for image style transfer from "Adaptive Convolutions for Structure-

65 Dec 22, 2022
Numerical Methods with Python, Numpy and Matplotlib

Numerical Bric-a-Brac Collections of numerical techniques with Python and standard computational packages (Numpy, SciPy, Numba, Matplotlib ...). Diffe

Vincent Bonnet 10 Dec 20, 2021
PenguinSpeciesPredictionML - Basic model to predict Penguin species based on beak size and sex.

Penguin Species Prediction (ML) 🐧 👨🏽‍💻 What? 💻 This project is a basic model using sklearn methods to predict Penguin species based on beak size

Tucker Paron 0 Jan 08, 2022
TeachMyAgent is a testbed platform for Automatic Curriculum Learning methods in Deep RL.

TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL Paper Website Documentation TeachMyAgent is a testbed platform for Automatic Cu

Flowers Team 51 Dec 25, 2022
Resources for the Ki testnet challenge

Ki Testnet Challenge This repository hosts ki-testnet-challenge. A set of scripts and resources to be used for the Ki Testnet Challenge What is the te

Ki Foundation 23 Aug 08, 2022
TAUFE: Task-Agnostic Undesirable Feature DeactivationUsing Out-of-Distribution Data

A deep neural network (DNN) has achieved great success in many machine learning tasks by virtue of its high expressive power. However, its prediction can be easily biased to undesirable features, whi

KAIST Data Mining Lab 8 Dec 07, 2022
A library for performing coverage guided fuzzing of neural networks

TensorFuzz: Coverage Guided Fuzzing for Neural Networks This repository contains a library for performing coverage guided fuzzing of neural networks,

Brain Research 195 Dec 28, 2022
Few-Shot Object Detection via Association and DIscrimination

Few-Shot Object Detection via Association and DIscrimination Code release of our NeurIPS 2021 paper: Few-Shot Object Detection via Association and DIs

Cao Yuhang 49 Dec 18, 2022
DualGAN-tensorflow: tensorflow implementation of DualGAN

ICCV paper of DualGAN DualGAN: unsupervised dual learning for image-to-image translation please cite the paper, if the codes has been used for your re

Jack Yi 252 Nov 10, 2022
BoxInst: High-Performance Instance Segmentation with Box Annotations

Introduction This repository is the code that needs to be submitted for OpenMMLab Algorithm Ecological Challenge, the paper is BoxInst: High-Performan

88 Dec 21, 2022
CAMoE + Dual SoftMax Loss (DSL): Improving Video-Text Retrieval by Multi-Stream Corpus Alignment and Dual Softmax Loss

CAMoE + Dual SoftMax Loss (DSL): Improving Video-Text Retrieval by Multi-Stream Corpus Alignment and Dual Softmax Loss This is official implement of "

程星 87 Dec 24, 2022
Keep CALM and Improve Visual Feature Attribution

Keep CALM and Improve Visual Feature Attribution Jae Myung Kim1*, Junsuk Choe1*, Zeynep Akata2, Seong Joon Oh1† * Equal contribution † Corresponding a

NAVER AI 90 Dec 07, 2022
✅ How Robust are Fact Checking Systems on Colloquial Claims?. In NAACL-HLT, 2021.

How Robust are Fact Checking Systems on Colloquial Claims? Official PyTorch implementation of our NAACL paper: Byeongchang Kim*, Hyunwoo Kim*, Seokhee

Byeongchang Kim 19 Mar 15, 2022
《Deep Single Portrait Image Relighting》(ICCV 2019)

Ratio Image Based Rendering for Deep Single-Image Portrait Relighting [Project Page] This is part of the Deep Portrait Relighting project. If you find

62 Dec 21, 2022
Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation

Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation Paper Multi-Target Adversarial Frameworks for Domain Adaptation in

Valeo.ai 20 Jun 21, 2022