VIsually-Pivoted Audio and(N) Text

Related tags

Deep Learningvipant
Overview

VIP-ANT: VIsually-Pivoted Audio and(N) Text

Code for the paper Connecting the Dots between Audio and Text without Parallel Data through Visual Knowledge Transfer.

VIP-ANT pivots audio and text via visual imagination.

Data

AudioSet can be downloaded and preprocessed via this tool.

Vision-Audio (VA) Pre-training

Check out the running script bash/run_bimodal_va.sh.

Audio-Text (AT) Fine-tuning

Check out the running script bash/run_bimodal_at.sh.

Dependencies

Dockerfile defines the minimum dependencies of the repo.

Citing VIP-ANT

@misc{vip-ant,
      title={Connecting the Dots between Audio and Text without Parallel Data through Visual Knowledge Transfer},
      author={Yanpeng Zhao and Jack Hessel and Youngjae Yu and Ximing Lu and Rowan Zellers and Yejin Choi},
      url={https://arxiv.org/abs/2112.08995},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      eprint={2112.08995},
      year={2021},
}

License

MIT

《LXMERT: Learning Cross-Modality Encoder Representations from Transformers》(EMNLP 2020)

The Most Important Thing. Our code is developed based on: LXMERT: Learning Cross-Modality Encoder Representations from Transformers

53 Dec 16, 2022
[CVPR 2021] Forecasting the panoptic segmentation of future video frames

Panoptic Segmentation Forecasting Colin Graber, Grace Tsai, Michael Firman, Gabriel Brostow, Alexander Schwing - CVPR 2021 [Link to paper] We propose

Niantic Labs 44 Nov 29, 2022
Manifold-Mixup implementation for fastai V2

Manifold Mixup Unofficial implementation of ManifoldMixup (Proceedings of ICML 19) for fast.ai (V2) based on Shivam Saboo's pytorch implementation of

Nestor Demeure 16 Jul 25, 2022
A Light in the Dark: Deep Learning Practices for Industrial Computer Vision

A Light in the Dark: Deep Learning Practices for Industrial Computer Vision This is the repository for our Paper/Contribution to the WI2022 in Nürnber

Maximilian Harl 6 Jan 17, 2022
Image Segmentation and Object Detection in Pytorch

Image Segmentation and Object Detection in Pytorch Pytorch-Segmentation-Detection is a library for image segmentation and object detection with report

Daniil Pakhomov 732 Dec 10, 2022
x-transformers-paddle 2.x version

x-transformers-paddle x-transformers-paddle 2.x version paddle 2.x版本 https://github.com/lucidrains/x-transformers 。 requirements paddlepaddle-gpu==2.2

yujun 7 Dec 08, 2022
This code implements constituency parse tree aggregation

README This code implements constituency parse tree aggregation. Folder details code: This folder contains the code that implements constituency parse

Adithya Kulkarni 0 Oct 11, 2021
Object DGCNN and DETR3D, Our implementations are built on top of MMdetection3D.

Object DGCNN & DETR3D This repo contains the implementations of Object DGCNN (https://arxiv.org/abs/2110.06923) and DETR3D (https://arxiv.org/abs/2110

Wang, Yue 539 Jan 07, 2023
GBIM(Gesture-Based Interaction map)

手势交互地图 GBIM(Gesture-Based Interaction map),基于视觉深度神经网络的交互地图,通过电脑摄像头观察使用者的手势变化,进而控制地图进行简单的交互。网络使用PaddleX提供的轻量级模型PPYOLO Tiny以及MobileNet V3 small,使得整个模型大小约10MB左右,即使在CPU下也能快速定位和识别手势。

8 Feb 10, 2022
The official repository for BaMBNet

BaMBNet-Pytorch Paper

Junjun Jiang 18 Dec 04, 2022
Keras-tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation(Unfinished)

Keras-FCN Fully convolutional networks and semantic segmentation with Keras. Models Models are found in models.py, and include ResNet and DenseNet bas

645 Dec 29, 2022
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Bayesian Neural Networks Pytorch implementations for the following approximate inference methods: Bayes by Backprop Bayes by Backprop + Local Reparame

1.4k Jan 07, 2023
Python interface for the DIGIT tactile sensor

DIGIT-INTERFACE Python interface for the DIGIT tactile sensor. For updates and discussions please join the #DIGIT channel at the www.touch-sensing.org

Facebook Research 35 Dec 22, 2022
Wanli Li and Tieyun Qian: Exploit a Multi-head Reference Graph for Semi-supervised Relation Extraction, IJCNN 2021

MRefG Wanli Li and Tieyun Qian: "Exploit a Multi-head Reference Graph for Semi-supervised Relation Extraction", IJCNN 2021 1. Requirements To reproduc

万理 5 Jul 26, 2022
Self-Supervised Multi-Frame Monocular Scene Flow (CVPR 2021)

Self-Supervised Multi-Frame Monocular Scene Flow 3D visualization of estimated depth and scene flow (overlayed with input image) from temporally conse

Visual Inference Lab @TU Darmstadt 85 Dec 22, 2022
[ICCV'21] Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment

CKDN The official implementation of the ICCV2021 paper "Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment" O

Multimedia Research 50 Dec 13, 2022
A general-purpose encoder-decoder framework for Tensorflow

READ THE DOCUMENTATION CONTRIBUTING A general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summariz

Google 5.5k Jan 07, 2023
Official PyTorch implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation

U-GAT-IT — Official PyTorch Implementation : Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Imag

Hyeonwoo Kang 2.4k Jan 04, 2023