null

Overview

DeformingThings4D dataset

Video | Paper

DeformingThings4D is an synthetic dataset containing 1,972 animation sequences spanning 31 categories of humanoids and animals.

Alt text

Animation file (.anime)

An animation example. Colors indicate dense correspondence Alt text

We store an animation sequence in the .anime file. The first frame is the canonical frame for which we store its triangle mesh. From the 2nd to the last frame, we store the 3D offsets of the mesh vertices.

#length         #type       #contents
|1              |int32      |nf: number of frames in the animation 
|1              |int32      |nv: number of vertices in the mesh (mesh topology fixed through frames)
|1              |int32      |nt: number of triangle face in the mesh
|nv*3           |float32    |vertice data of the 1st frame (3D positions in x-y-z-order)
|nt*3           |int32      |triangle face data of the 1st frame
|(nf-1)*nv*3    |float32    |3D offset data from the 2nd to the last frame

1,972 animations

Currently, we provide 200 animations for humanoids and 1772 animations for animals. The followings show the structure of the dataset. The screenshots show the animations in the dataset.

|---|--humanoids (200 animations, 34228 frames)
    |   |--clarie_run  #a animation folder [objectID]_[ActionID])
    |       |--clarie_run.anime # animation file, storing per-frame shape and
    |       |--screenshots # screenshots of animation
    |       |--clarie_run.fbx # raw blender animation file, only available for humanoids
    |--animals (1772 animations, 88137 frames)

Alt text

Use case of the dataset

The dataset is designed to tackle the following tasks using data-driven approaches

The dataset generalizes well to real-world scans. The following shows real-world scene flow estimation and 4dcomplete results using models that are trained with this dataset.

Alt text

Download Data

Currently, we provide the .anime files for all 1972 animations. If you would like to download the DeformingThings4D data, please fill out this google form, and, once accepted, we will send you the link to download the data.

We can also provide blender-generated scene flow & RGBD sequences and volume data upon request. You can also generate these data from the .anime files using the Blender scripts.

Citation

If you use DeformingThings4D data or code please cite:

@article{li20214dcomplete, 
    title={4dcomplete: Non-rigid motion estimation beyond the observable surface.}, 
    author={Yang Li, Hikari Takehara, Takafumi Taketomi, Bo Zheng, and Matthias Nießner},
    journal={IEEE International Conference on Computer Vision (ICCV)},
    year={2021}
}

Help

If you have any questions, please contact us at [email protected], or open an issue at Github.

License

The data is released under DeformingThings4D Terms of Use, and the code is release under a non-comercial creative commons license.

🛠 All-in-one web-based IDE specialized for machine learning and data science.

All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu

Machine Learning Tooling 2.9k Jan 09, 2023
SOTA model in CIFAR10

A PyTorch Implementation of CIFAR Tricks 调研了CIFAR10数据集上各种trick,数据增强,正则化方法,并进行了实现。目前项目告一段落,如果有更好的想法,或者希望一起维护这个项目可以提issue或者在我的主页找到我的联系方式。 0. Requirement

PJDong 58 Dec 21, 2022
using yolox+deepsort for object-tracker

YOLOX_deepsort_tracker yolox+deepsort实现目标跟踪 最新的yolox尝尝鲜~~(yolox正处在频繁更新阶段,因此直接链接yolox仓库作为子模块) Install Clone the repository recursively: git clone --rec

245 Dec 26, 2022
Weight initialization schemes for PyTorch nn.Modules

nninit Weight initialization schemes for PyTorch nn.Modules. This is a port of the popular nninit for Torch7 by @kaixhin. ##Update This repo has been

Alykhan Tejani 69 Jan 26, 2021
Understanding the Generalization Benefit of Model Invariance from a Data Perspective

Understanding the Generalization Benefit of Model Invariance from a Data Perspective This is the code for our NeurIPS2021 paper "Understanding the Gen

1 Jan 15, 2022
Implementation of temporal pooling methods studied in [ICIP'20] A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment

Implementation of temporal pooling methods studied in [ICIP'20] A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment

Zhengzhong Tu 5 Sep 16, 2022
This is the official PyTorch implementation of our paper: "Artistic Style Transfer with Internal-external Learning and Contrastive Learning".

Artistic Style Transfer with Internal-external Learning and Contrastive Learning This is the official PyTorch implementation of our paper: "Artistic S

51 Dec 20, 2022
Jittor implementation of PCT:Point Cloud Transformer

PCT: Point Cloud Transformer This is a Jittor implementation of PCT: Point Cloud Transformer.

MenghaoGuo 547 Jan 03, 2023
Official implementation of Deep Convolutional Dictionary Learning for Image Denoising.

DCDicL for Image Denoising Hongyi Zheng*, Hongwei Yong*, Lei Zhang, "Deep Convolutional Dictionary Learning for Image Denoising," in CVPR 2021. (* Equ

Z80 91 Dec 21, 2022
Bagua is a flexible and performant distributed training algorithm development framework.

Bagua is a flexible and performant distributed training algorithm development framework.

786 Dec 17, 2022
Learning to Stylize Novel Views

Learning to Stylize Novel Views [Project] [Paper] Contact: Hsin-Ping Huang ([ema

34 Nov 27, 2022
PyTorch implementation of Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network

hierarchical-multi-label-text-classification-pytorch Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach This

Mingu Kang 17 Dec 13, 2022
Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging

Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging This repository contains an implementation

Computational Photography Lab @ SFU 1.1k Jan 02, 2023
PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020).

Scaffold-Federated-Learning PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020). Environment numpy=

KI 30 Dec 29, 2022
AI assistant built in python.the features are it can display time,say weather,open-google,youtube,instagram.

AI assistant built in python.the features are it can display time,say weather,open-google,youtube,instagram.

AK-Shanmugananthan 1 Nov 29, 2021
Artificial Intelligence playing minesweeper 🤖

AI playing Minesweeper ✨ Minesweeper is a single-player puzzle video game. The objective of the game is to clear a rectangular board containing hidden

Vaibhaw 8 Oct 17, 2022
Official implementation of "StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation" (SIGGRAPH 2021)

StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation This repository contains the official PyTorch implementation of the following

Wonjong Jang 270 Dec 30, 2022
Repository for the electrical and ICT benchmark model developed in the ERIGrid 2.0 project.

Benchmark Model Electrical and ICT System This repository contains the documentation, code, and models for the electrical and ICT benchmark model deve

ERIGrid 2.0 1 Nov 29, 2021
Code for paper: "Spinning Language Models for Propaganda-As-A-Service"

Spinning Language Models for Propaganda-As-A-Service This is the source code for the Arxiv version of the paper. You can use this Google Colab to expl

Eugene Bagdasaryan 16 Jan 03, 2023
Official code for Next Check-ins Prediction via History and Friendship on Location-Based Social Networks (MDM 2018)

MUC Next Check-ins Prediction via History and Friendship on Location-Based Social Networks (MDM 2018) Performance Details for Accuracy: | Dataset

Yijun Su 3 Oct 09, 2022