BABEL: Bodies, Action and Behavior with English Labels [CVPR 2021]

Related tags

Deep LearningBABEL
Overview

BABEL: Bodies, Action and Behavior with English Labels [CVPR 2021]

Abhinanda R. Punnakkal*, Arjun Chandrasekaran*, Nikos Athanasiou, Alejandra Quiros-Ramirez, Michael J. Black. * denotes equal contribution

Project Website | Paper | Video | Poster


BABEL is a large dataset with language labels describing the actions being performed in mocap sequences. BABEL labels about 43 hours of mocap sequences from AMASS [1] with action labels. Sequences have action labels at two possible levels of abstraction:

  • Sequence labels which describe the overall action in the sequence
  • Frame labels which describe all actions in every frame of the sequence. Each frame label is precisely aligned with the duration of the corresponding action in the mocap sequence, and multiple actions can overlap.

To download the BABEL action labels, visit our 'Data' page. You can download the mocap sequences from AMASS.

Tutorials

We release some helper code in Jupyter notebooks to load the BABEL dataset, visualize mocap sequences and their action labels, search BABEL for sequences containing specific actions, etc.

See notebooks/ for more details.

Action Recognition

We provide features, training and inference code, and pre-trained checkpoints for 3D skeleton-based action recognition.

Please see action_recognition/ for more details.

Acknowledgements

The notebooks in this repo are inspired by the those provided by AMASS. The Action Recognition code is based on the 2s-AGCN implementation.

References

[1] Mahmood, Naureen, et al. "AMASS: Archive of motion capture as surface shapes." Proceedings of the IEEE/CVF International Conference on Computer Vision. 2019.

License

Software Copyright License for non-commercial scientific research purposes. Please read carefully the terms and conditions and any accompanying documentation before you download and/or use the AMASS dataset, and software, (the "Model & Software"). By downloading and/or using the Model & Software (including downloading, cloning, installing, and any other use of this GitHub repository), you acknowledge that you have read these terms and conditions, understand them, and agree to be bound by them. If you do not agree with these terms and conditions, you must not download and/or use the Model & Software. Any infringement of the terms of this agreement will automatically terminate your rights under this License.

Contact

The code in this repository is developed by Abhinanda Punnakkal and Arjun Chandrasekaran.

If you have any questions you can contact us at [email protected].

Code for A Volumetric Transformer for Accurate 3D Tumor Segmentation

VT-UNet This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmentaion results of VT-UNet. Environmen

Himashi Amanda Peiris 114 Dec 20, 2022
AdelaiDepth is an open source toolbox for monocular depth prediction.

AdelaiDepth is an open source toolbox for monocular depth prediction.

Adelaide Intelligent Machines (AIM) Group 743 Jan 01, 2023
Implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs".

PPO-BiHyb This is the official implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Grap

<a href=[email protected]"> 66 Nov 23, 2022
Playable Video Generation

Playable Video Generation Playable Video Generation Willi Menapace, Stéphane Lathuilière, Sergey Tulyakov, Aliaksandr Siarohin, Elisa Ricci Paper: ArX

Willi Menapace 136 Dec 31, 2022
The official PyTorch implementation of paper BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition

BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition Boyan Zhou, Quan Cui, Xiu-Shen Wei*, Zhao-Min Chen This repo

Megvii-Nanjing 616 Dec 21, 2022
Official implementation of "A Unified Objective for Novel Class Discovery", ICCV2021 (Oral)

A Unified Objective for Novel Class Discovery This is the official repository for the paper: A Unified Objective for Novel Class Discovery Enrico Fini

Enrico Fini 118 Dec 26, 2022
Keras implementation of Deeplab v3+ with pretrained weights

Keras implementation of Deeplabv3+ This repo is not longer maintained. I won't respond to issues but will merge PR DeepLab is a state-of-art deep lear

1.3k Dec 07, 2022
Official PyTorch implementation of SyntaSpeech (IJCAI 2022)

SyntaSpeech: Syntax-Aware Generative Adversarial Text-to-Speech | | | | 中文文档 This repository is the official PyTorch implementation of our IJCAI-2022

Zhenhui YE 116 Nov 24, 2022
Distributing reference energies for SMIRNOFF implementations

Warning: This code is currently experimental and under active development. Is it not yet suitable for distribution or use as reference implementation.

Open Force Field Initiative 1 Dec 07, 2021
CBKH: The Cornell Biomedical Knowledge Hub

Cornell Biomedical Knowledge Hub (CBKH) CBKG integrates data from 18 publicly available biomedical databases. The current version of CBKG contains a t

44 Dec 21, 2022
A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval

CLIP4CMR A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval The original data and pre-calculate

24 Dec 26, 2022
GT China coal model

GT China coal model The full version of a China coal transport model with a very high spatial reslution. What it does The code works in a few steps: T

0 Dec 13, 2021
Neighborhood Contrastive Learning for Novel Class Discovery

Neighborhood Contrastive Learning for Novel Class Discovery This repository contains the official implementation of our paper: Neighborhood Contrastiv

Zhun Zhong 56 Dec 09, 2022
DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style Editing

DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style Editing Figure: Joint multi-attribute edits using DyStyle model. Great diversity

74 Dec 03, 2022
BABEL: Bodies, Action and Behavior with English Labels [CVPR 2021]

BABEL is a large dataset with language labels describing the actions being performed in mocap sequences. BABEL labels about 43 hours of mocap sequences from AMASS [1] with action labels.

113 Dec 28, 2022
Fast RFC3339 compliant Python date-time library

udatetime: Fast RFC3339 compliant date-time library Handling date-times is a painful act because of the sheer endless amount of formats used by people

Simon Pirschel 235 Oct 25, 2022
Real-time analysis of intracranial neurophysiology recordings.

py_neuromodulation Click this button to run the "Tutorial ML with py_neuro" notebooks: The py_neuromodulation toolbox allows for real time capable pro

Interventional Cognitive Neuromodulation - Neumann Lab Berlin 15 Nov 03, 2022
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks

StackGAN Pytorch implementation Inception score evaluation StackGAN-v2-pytorch Tensorflow implementation for reproducing main results in the paper Sta

Han Zhang 1.8k Dec 21, 2022
Secure Distributed Training at Scale

Secure Distributed Training at Scale This repository contains the implementation of experiments from the paper "Secure Distributed Training at Scale"

Yandex Research 9 Jul 11, 2022
The codes and models in 'Gaze Estimation using Transformer'.

GazeTR We provide the code of GazeTR-Hybrid in "Gaze Estimation using Transformer". We recommend you to use data processing codes provided in GazeHub.

65 Dec 27, 2022