implicit displacement field

Related tags

Deep Learningidf
Overview

Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields

[project page][paper][cite]

overview

overview video

demos

cuda 11.1 and pytorch 3.8

preparations

git clone https://github.com/yifita/idf.git
cd idf

# conda environment and dependencies
# update conda
conda update -n base -c defaults conda
# install requirements
conda env create --name idf -f environment.yml
conda activate idf

# download data. This will download 8 mesh and point clouds to data/benchmark_shapes
sh data/get_data.sh

surface reconstruction

# surface reconstruction from point cloud
# replace {asian_dragon} with another model name inside the benchmark_shape folder
python net/classes/runner.py net/experiments/displacement_benchmark/ablation/ablation_phased_scaledTanh_yes_act_yes_baseLoss_yes.json --name asian_dragon

detail transfer

This example uses provided base shapes

sh data/get_dt_shapes.sh
python net/classes/runner.py net/experiments/displacement_benchmark/transfer/shorts_2phase.json

bibtex

@misc{yifan2021geometryconsistent,
      title={Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields},
      author={Wang Yifan and Lukas Rahmann and Olga Sorkine-Hornung},
      year={2021},
      eprint={2106.05187},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}
Owner
Yifan Wang
PhD student @ ETH Zurich
Yifan Wang
PyTorch implementation for our paper Learning Character-Agnostic Motion for Motion Retargeting in 2D, SIGGRAPH 2019

Learning Character-Agnostic Motion for Motion Retargeting in 2D We provide PyTorch implementation for our paper Learning Character-Agnostic Motion for

Rundi Wu 367 Dec 22, 2022
[NeurIPS 2021] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining

COCO-LM This repository contains the scripts for fine-tuning COCO-LM pretrained models on GLUE and SQuAD 2.0 benchmarks. Paper: COCO-LM: Correcting an

Microsoft 106 Dec 12, 2022
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition, CVPR 2018

PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place

Mikaela Uy 294 Dec 12, 2022
ThunderGBM: Fast GBDTs and Random Forests on GPUs

Documentations | Installation | Parameters | Python (scikit-learn) interface What's new? ThunderGBM won 2019 Best Paper Award from IEEE Transactions o

Xtra Computing Group 647 Jan 04, 2023
Writeups for the challenges from DownUnderCTF 2021

cloud Challenge Author Difficulty Release Round Bad Bucket Blue Alder easy round 1 Not as Bad Bucket Blue Alder easy round 1 Lost n Found Blue Alder m

DownUnderCTF 161 Dec 31, 2022
Continual World is a benchmark for continual reinforcement learning

Continual World Continual World is a benchmark for continual reinforcement learning. It contains realistic robotic tasks which come from MetaWorld. Th

41 Dec 24, 2022
Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.

Neural Spatio-Temporal Point Processes [arxiv] Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel Abstract. We propose a new class of parameterizations

Facebook Research 75 Dec 19, 2022
Async API for controlling Hue Lights

Hue API Async API for controlling Hue Lights Documentation: hue-api.nirantak.com Source: github.com/nirantak/hue-api Installation This is an async cli

Nirantak Raghav 4 Nov 16, 2022
DCSL - Generalizable Crowd Counting via Diverse Context Style Learning

DCSL Generalizable Crowd Counting via Diverse Context Style Learning Requirement

3 Jun 13, 2022
Semantic Segmentation of images using PixelLib with help of Pascalvoc dataset trained with Deeplabv3+ framework.

CARscan- Approach 1 - Segmentation of images by detecting contours. It failed because in images with elements along with cars were also getting detect

Padmanabha Banerjee 5 Jul 29, 2021
Distributed DataLoader For Pytorch Based On Ray

Dpex——用户无感知分布式数据预处理组件 一、前言 随着GPU与CPU的算力差距越来越大以及模型训练时的预处理Pipeline变得越来越复杂,CPU部分的数据预处理已经逐渐成为了模型训练的瓶颈所在,这导致单机的GPU配置的提升并不能带来期望的线性加速。预处理性能瓶颈的本质在于每个GPU能够使用的C

Dalong 23 Nov 02, 2022
3DV 2021: Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry

SynergyNet 3DV 2021: Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry Cho-Ying Wu, Qiangeng Xu, Ulrich Neumann, CGIT Lab at Unive

Cho-Ying Wu 239 Jan 06, 2023
Generative Query Network (GQN) in PyTorch as described in "Neural Scene Representation and Rendering"

Update 2019/06/24: A model trained on 10% of the Shepard-Metzler dataset has been added, the following notebook explains the main features of this mod

Jesper Wohlert 313 Dec 27, 2022
Backdoor Attack through Frequency Domain

Backdoor Attack through Frequency Domain DEPENDENCIES python==3.8.3 numpy==1.19.4 tensorflow==2.4.0 opencv==4.5.1 idx2numpy==1.2.3 pytorch==1.7.0 Data

5 Jun 18, 2022
Code for "FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation".

FPS-Net Code for "FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation", accepted by ISPRS journal of Photogrammetry

15 Nov 30, 2022
Detectron2 is FAIR's next-generation platform for object detection and segmentation.

Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up r

Facebook Research 23.3k Jan 08, 2023
Joint Gaussian Graphical Model Estimation: A Survey

Joint Gaussian Graphical Model Estimation: A Survey Test Models Fused graphical lasso [1] Group graphical lasso [1] Graphical lasso [1] Doubly joint s

Koyejo Lab 1 Aug 10, 2022
Simple Baselines for Human Pose Estimation and Tracking

Simple Baselines for Human Pose Estimation and Tracking News Our new work High-Resolution Representations for Labeling Pixels and Regions is available

Microsoft 2.7k Jan 05, 2023
unet for image segmentation

Implementation of deep learning framework -- Unet, using Keras The architecture was inspired by U-Net: Convolutional Networks for Biomedical Image Seg

zhixuhao 4.1k Dec 31, 2022
Complete the code of prefix-tuning in low data setting

Prefix Tuning Note: 作者在论文中提到使用真实的word去初始化prefix的操作(Initializing the prefix with activations of real words,significantly improves generation)。我在使用作者提供的

Andrew Zeng 4 Jul 11, 2022