Educational API for 3D Vision using pose to control carton.

Overview

Pose2Carton

A educational project (e.g., using 3D pose to control 3D carton) for learning 3D vision (application of human mesh recovery) or imitation learning

Update Notes

2021/06/08: Update the requirement for your code submission on github

2021/05/20: Update the saving logic of mapping results(.pkl). In previous version, pkl will not be overwritten, so if you try mapping multiple times, the pkl will stay as it was in previous mapping. This problem is fixed now, pls ensure that your results/ is the latest version

2021/05/17: Add quick start instructions to help you dive into this project & Use custom obj loader instead of open3d

Requirements

  • code only tested on linux system (ubuntu 16.04)
  • open3d==0.11.0(if you want to try online models, use open3d 0.10.0 along with your own video recording tool to save visualization)
  • tqdm
  • opencv-python

pip install -r requirements.txt (anaconda recommended, python3)

Tutorials

Code structure

  • transfer.py: the main mapping file
  • vis.py: visualize the mapping sequence of the corresponding mesh
  • pose_samples: some samples of SMPL model for one frame
  • obj_seq_id: some samples of SMPL model for temporal sequence

Method

image

Project Result

image

Visulization

Run vis.py (to get more clear visualization, press ctrl + 1 / ctrl + 2 / ctrl + 3 ...)

image

LICENSE

The code is under Apache-2.0 License.

For EE228 students from SJTU

Please read course project requirements.

Owner
PhD candidate in machine learning, with emphasis on Human Reconstruction and VR.
SuRE Evaluation: A Supplementary Material

SuRE Evaluation: A Supplementary Material This repository contains supplementary material regarding the evaluations presented in the paper Visual Expl

NYU Visualization Lab 0 Dec 14, 2021
Clairvoyance: a Unified, End-to-End AutoML Pipeline for Medical Time Series

Clairvoyance: A Pipeline Toolkit for Medical Time Series Authors: van der Schaar Lab This repository contains implementations of Clairvoyance: A Pipel

van_der_Schaar \LAB 89 Dec 07, 2022
TLDR: Twin Learning for Dimensionality Reduction

TLDR (Twin Learning for Dimensionality Reduction) is an unsupervised dimensionality reduction method that combines neighborhood embedding learning with the simplicity and effectiveness of recent self

NAVER 105 Dec 28, 2022
Using Self-Supervised Pretext Tasks for Active Learning - Official Pytorch Implementation

Using Self-Supervised Pretext Tasks for Active Learning - Official Pytorch Implementation Experiment Setting: CIFAR10 (downloaded and saved in ./DATA

John Seon Keun Yi 38 Dec 27, 2022
This repository accompanies our paper “Do Prompt-Based Models Really Understand the Meaning of Their Prompts?”

This repository accompanies our paper “Do Prompt-Based Models Really Understand the Meaning of Their Prompts?” Usage To replicate our results in Secti

Albert Webson 64 Dec 11, 2022
Code for IntraQ, PyTorch implementation of our paper under review

IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization paper Requirements Python = 3.7.10 Pytorch == 1.7

1 Nov 19, 2021
General purpose Slater-Koster tight-binding code for electronic structure calculations

tight-binder Introduction General purpose tight-binding code for electronic structure calculations based on the Slater-Koster approximation. The code

9 Dec 15, 2022
PyTorch code accompanying our paper on Maximum Entropy Generators for Energy-Based Models

Maximum Entropy Generators for Energy-Based Models All experiments have tensorboard visualizations for samples / density / train curves etc. To run th

Rithesh Kumar 135 Oct 27, 2022
Tensorflow/Keras Plug-N-Play Deep Learning Models Compilation

DeepBay This project was created with the objective of compile Machine Learning Architectures created using Tensorflow or Keras. The architectures mus

Whitman Bohorquez 4 Sep 26, 2022
Adaptive Prototype Learning and Allocation for Few-Shot Segmentation (CVPR 2021)

ASGNet The code is for the paper "Adaptive Prototype Learning and Allocation for Few-Shot Segmentation" (accepted to CVPR 2021) [arxiv] Overview data/

Gen Li 91 Dec 23, 2022
Official repository for "Intriguing Properties of Vision Transformers" (2021)

Intriguing Properties of Vision Transformers Muzammal Naseer, Kanchana Ranasinghe, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, & Ming-Hsuan Yang P

Muzammal Naseer 155 Dec 27, 2022
UltraGCN: An Ultra Simplification of Graph Convolutional Networks for Recommendation

UltraGCN This is our Pytorch implementation for our CIKM 2021 paper: Kelong Mao, Jieming Zhu, Xi Xiao, Biao Lu, Zhaowei Wang, Xiuqiang He. UltraGCN: A

XUEPAI 93 Jan 03, 2023
Creating multimodal multitask models

Fusion Brain Challenge The English version of the document can be found here. Обновления 01.11 Мы выкладываем пример данных, аналогичных private test

Sber AI 43 Nov 28, 2022
This is the code of using DQN to play Sekiro .

Update for using DQN to play sekiro 2021.2.2(English Version) This is the code of using DQN to play Sekiro . I am very glad to tell that I have writen

144 Dec 25, 2022
Experiments with differentiable stacks and queues in PyTorch

Please use stacknn-core instead! StackNN This project implements differentiable stacks and queues in PyTorch. The data structures are implemented in s

Will Merrill 141 Oct 06, 2022
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-tree Complex Wavelet Representation and Contradict Channel Loss (HDCWNet)

ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-tree Complex Wavelet Representation and Contradict Channel Loss (HDCWNet) (

Wei-Ting Chen 49 Dec 27, 2022
Official code repository for "Exploring Neural Models for Query-Focused Summarization"

Query-Focused Summarization Official code repository for "Exploring Neural Models for Query-Focused Summarization" This is a work in progress. Expect

Salesforce 29 Dec 18, 2022
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.

AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, an

VITA 112 Nov 07, 2022
GAN Image Generator and Characterwise Image Recognizer with python

MODEL SUMMARY 모델의 구조는 크게 6단계로 나뉩니다. STEP 0: Input Image Predict 할 이미지를 모델에 입력합니다. STEP 1: Make Black and White Image STEP 1 은 입력받은 이미지의 글자를 흑색으로, 배경을

Juwan HAN 1 Feb 09, 2022
Model-based 3D Hand Reconstruction via Self-Supervised Learning, CVPR2021

S2HAND: Model-based 3D Hand Reconstruction via Self-Supervised Learning S2HAND presents a self-supervised 3D hand reconstruction network that can join

Yujin Chen 72 Dec 12, 2022