Human motion synthesis using Unity3D

Overview

Human motion synthesis using Unity3D

Prerequisite:

Software: amc2bvh.exe, Unity 2017, Blender.
Unity: RockVR (Video Capture), scenes, character models Files:
Motion files: amc, asf or bvh formats.
Character models: fbx format.

Procedure

  1. If motion files in amc/asf format, run amc2bvh.exe to convert them to bvh
  2. Place all bvh files into "Desktop/New folder/bvh" (or modify script)
  3. Open Blender and run the bvh2fbx.py script. It will convert the motion files to fbx format which Unity can process and place them under the unity "Resources/Input"[1]
  4. Find the imported motion file in Unity and change its Animation Type to Humanoid under Rig. Check to make sure the model is mapped properly.
  5. Configure the different variations to record video (characters, camera angle, scene, lighting)
    1. For characters, add[2] or remove from the "characters" GameObject in Unity Editor for the ones desired. For new character added to the scene, add the "New Animation Controller"[3] in Asset to the character's controller in the "Animator" section.
    2. For camera, change the position of the DedicatedCapture GameObjects to the desired location. Add additional DedicatedCapture GameObjects for more angle. Read the documentation for RockVR Video Capture for more detail.
    3. For scene, check the desired scenes within the intro scene and run.
    4. For lighting, change the "lights" parameter in Automation.cs script. Add more values to the array for more variations in lighting angles.
  6. Start up the "intro" scene and run it from Unity Editor. Click "Start" button to start the problem.
  7. Adjust the desired resolution and framerate and click start. For initial run, leave all the counters to 0. For continuing runs enter the counters where the previous run left off. The videos will be recorded to "Documents/RockVR/Video"[4]

Note

  • [1] Converting too many bvh files at a time may result in Blender crashing. Try converting them in batches of smaller quantity (~50).
  • [2] To add a GameObject to a Scene in Unity, drag it from the Asset menu to a position in the Hierarchy menu or a position in the scene itself. You can also create an empty GameObject from the "GameObject->Create Empty" option.
  • [3] Depending on the framerate of the motion files, you may need to adjust the speed of the animation. To do this go to "Assets" and find the "New Animator Controller" and open it. Then click on "New State" and adjust the speed to framerate/24 (if 120 frames changes to 5, if 60 change to 2.5, etc). Also find the line "timeLeft = ((AnimationClip)clips[clipCounter]).length;" in the SwitchAnimation function and divide it by the speed.
  • [4] Unity will most likely freeze or crash if left running for too long. Adjust the counters in the "intro" scene to resume progress.

Scene Creation procedure

  1. To get a scene, either download a pre-built one or build one yourself using various 3d models for GameObjects.
  2. Create an empty GameObject named "characters" and place it at a location best suited for recording. Add a character to it to see if any adjusting or scaling is needed.
  3. Add DedicatedCapture GameObjects from the "RockVR/Video/Prefabs" folder to the scene in desired locations.
  4. Attach the AudioCapture script in "RockVR/Video/Scripts" folder to the main camera.
  5. Create an empty GameObject named "VideoCaptureCtrl" and attach the VideoCaptureCtrl script in "RockVR/Video/Scripts" to it. Also attach the Automation.cs script from "Scripts" to it as well.
  6. Add the first DedicatedCapture GameObject as well as the AudioCapture to the the VideoCaptureCtrl script.
  7. If there is no "Directional light" GameObject, create one.
  8. Add the created scene to build settings.
  9. Add a check box in the intro scene for the newly created scene and modify the scene "ProcessParameter" accordingly.

Additional characters

In the "characters" folder in Assets, there is a list of preprocessed characters I got from the Unity asset store for free.
To process new characters:

  1. Change its Animation type to Humanoid under Rig
  2. Fix any mapping problem for the bones of the character
  3. Remove the mapping on the bones for both hands. This could be done using the "New Human Template" in the Assets folder. (This is to avoid weird finger mapping from the animations)

Instructions on error handling

  • If you tried to terminate the program insider the Unity Editor, the ffmpeg.exe will still be running and result in unfinished video and audio files to remain in the videos folder. To solve this issue, simply terminate the ffmpeg.exe from task manager and delete the unfinished files.
  • Since the program freezes fairly often, a temporary save state feature is implemented. Once Unity froze, terminate it from task manager. Look into the videos folder and figure out what combination the next video should be. Enter the parameters where the last run left off in the "intro" scene (various counters) to pick up from there.

Local environment specs

  • OS: Microsoft Windows 10 Pro
  • Version: 10.0.16299 Build 16299
  • Processor: Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz, 2201 Mhz, 10 Core(s), 20 Logical Processor(s)
  • Total Physical Memory: 63.9 GB
  • GPU: NVIDIA Quadro M5000
Owner
Hao Xu
Hao Xu
ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet, ICCV 2021 Update: 2021/03/11: update our new results. Now our T2T-ViT-14 w

YITUTech 1k Dec 31, 2022
MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving

MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving Code will be available soon. Motivation Architecture

Kai Chen 24 Apr 19, 2022
Official PyTorch Implementation of GAN-Supervised Dense Visual Alignment

GAN-Supervised Dense Visual Alignment — Official PyTorch Implementation Paper | Project Page | Video This repo contains training, evaluation and visua

944 Jan 07, 2023
Code release for "Detecting Twenty-thousand Classes using Image-level Supervision".

Detecting Twenty-thousand Classes using Image-level Supervision Detic: A Detector with image classes that can use image-level labels to easily train d

Meta Research 1.3k Jan 04, 2023
ROSITA: Enhancing Vision-and-Language Semantic Alignments via Cross- and Intra-modal Knowledge Integration

ROSITA News & Updates (24/08/2021) Release the demo to perform fine-grained semantic alignments using the pretrained ROSITA model. (15/08/2021) Releas

Vision and Language Group@ MIL 48 Dec 23, 2022
Official PyTorch Code of GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection (CVPR 2021)

GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Mo

Abhinav Kumar 76 Jan 02, 2023
Implementation for paper "STAR: A Structure-aware Lightweight Transformer for Real-time Image Enhancement" (ICCV 2021).

STAR-pytorch Implementation for paper "STAR: A Structure-aware Lightweight Transformer for Real-time Image Enhancement" (ICCV 2021). CVF (pdf) STAR-DC

43 Dec 21, 2022
Aggragrating Nested Transformer Official Jax Implementation

NesT is a simple method, which aggragrates nested local transformers on image blocks. The idea makes vision transformers attain better accuracy, data efficiency, and convergence on the ImageNet bench

Google Research 169 Dec 20, 2022
Complete U-net Implementation with keras

U Net Lowered with Keras Complete U-net Implementation with keras Original Paper Link : https://arxiv.org/abs/1505.04597 Special Implementations : The

Sagnik Roy 14 Oct 10, 2022
TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation

TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation Zhaoyun Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li

DamoCV 25 Dec 16, 2022
This repository comes with the paper "On the Robustness of Counterfactual Explanations to Adverse Perturbations"

Robust Counterfactual Explanations This repository comes with the paper "On the Robustness of Counterfactual Explanations to Adverse Perturbations". I

Marco 5 Dec 20, 2022
Paddle implementation for "Cross-Lingual Word Embedding Refinement by ℓ1 Norm Optimisation" (NAACL 2021)

L1-Refinement Paddle implementation for "Cross-Lingual Word Embedding Refinement by ℓ1 Norm Optimisation" (NAACL 2021) 🙈 A more detailed readme is co

Lincedo Lab 4 Jun 09, 2021
Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments

Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments Paper: arXiv (ICRA 2021) Video : https://youtu.be/CC

Sachini Herath 68 Jan 03, 2023
Human annotated noisy labels for CIFAR-10 and CIFAR-100.

Dataloader for CIFAR-N CIFAR-10N noise_label = torch.load('./data/CIFAR-10_human.pt') clean_label = noise_label['clean_label'] worst_label = noise_lab

<a href=[email protected]"> 117 Nov 30, 2022
StyleGAN2 Webtoon / Anime Style Toonify

StyleGAN2 Webtoon / Anime Style Toonify Korea Webtoon or Japanese Anime Character Stylegan2 base high Quality 1024x1024 / 512x512 Generate and Transfe

121 Dec 21, 2022
Nvidia Semantic Segmentation monorepo

Paper | YouTube | Cityscapes Score Pytorch implementation of our paper Hierarchical Multi-Scale Attention for Semantic Segmentation. Please refer to t

NVIDIA Corporation 1.6k Jan 04, 2023
Recursive Bayesian Networks

Recursive Bayesian Networks This repository contains the code to reproduce the results from the NeurIPS 2021 paper Lieck R, Rohrmeier M (2021) Recursi

Robert Lieck 11 Oct 18, 2022
Create Own QR code with Python

Create-Own-QR-code Create Own QR code with Python SO guys in here, you have to install pyqrcode 2. open CMD and type python -m pip install pyqrcode

JehanKandy 10 Jul 13, 2022
Codes for “A Deeply Supervised Attention Metric-Based Network and an Open Aerial Image Dataset for Remote Sensing Change Detection”

DSAMNet The pytorch implementation for "A Deeply-supervised Attention Metric-based Network and an Open Aerial Image Dataset for Remote Sensing Change

Mengxi Liu 41 Dec 14, 2022
Source code to accompany Defunctland's video "FASTPASS: A Complicated Legacy"

Shapeland Simulator Source code to accompany Defunctland's video "FASTPASS: A Complicated Legacy" Download the video at https://www.youtube.com/watch?

TouringPlans.com 70 Dec 14, 2022