Codes for the AAAI'22 paper "TransZero: Attribute-guided Transformer for Zero-Shot Learning"

Overview

TransZero [arXiv]

This repository contains the testing code for the paper "TransZero: Attribute-guided Transformer for Zero-Shot Learning" accepted to AAAI 2022. We will release all codes of this work later.

Preparing Dataset and Model

We provide trained models (Google Drive) on three different datasets: CUB, SUN, AWA2 in the CZSL/GZSL setting. You can download model files as well as corresponding datasets, and organize them as follows:

.
├── saved_model
│   ├── TransZero_CUB_CZSL.pth
│   ├── TransZero_CUB_GZSL.pth
│   ├── TransZero_SUN_CZSL.pth
│   ├── TransZero_SUN_GZSL.pth
│   ├── TransZero_AWA2_CZSL.pth
│   └── TransZero_AWA2_GZSL.pth
├── data
│   ├── CUB/
│   ├── SUN/
│   └── AWA2/
└── ···

Requirements

The code implementation of TransZero mainly based on PyTorch. All of our experiments run and test in Python 3.8.8. To install all required dependencies:

$ pip install -r requirements.txt

Runing

Runing following commands and testing TransZero on different dataset:

CUB Dataset:

$ python test.py --config config/CUB_CZSL.json      # CZSL Setting
$ python test.py --config config/CUB_GZSL.json      # GZSL Setting

SUN Dataset:

$ python test.py --config config/SUN_CZSL.json      # CZSL Setting
$ python test.py --config config/SUN_GZSL.json      # GZSL Setting

AWA2 Dataset:

$ python test.py --config config/AWA2_CZSL.json     # CZSL Setting
$ python test.py --config config/AWA2_GZSL.json     # GZSL Setting

Results

Results of our released models using various evaluation protocols on three datasets, both in the conventional ZSL (CZSL) and generalized ZSL (GZSL) settings.

Dataset Acc(CZSL) U(GZSL) S(GZSL) H(GZSL)
CUB 76.8 69.3 68.3 68.8
SUN 65.6 52.6 33.4 40.8
AWA2 70.1 61.3 82.3 70.2

Note: All of above results are run on a server with an AMD Ryzen 7 5800X CPU and a NVIDIA RTX A6000 GPU.

Citation

If this work is helpful for you, please cite our paper.

@InProceedings{Chen2021TransZero,
    author    = {Chen, Shiming and Hong, Ziming and Liu, Yang and Xie, Guo-Sen and Sun, Baigui and Li, Hao and Peng, Qinmu and Lu, Ke and You, Xinge},
    title     = {TransZero: Attribute-guided Transformer for Zero-Shot Learning},
    booktitle = {Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI)},
    year      = {2022}
}

References

Parts of our codes based on:

Contact

If you have any questions about codes, please don't hesitate to contact us by [email protected] or [email protected].

Owner
Shiming Chen
Interest: Generative modeling and learning, zero-shot learning, image retrieval, domain adaptation
Shiming Chen
Seq2seq - Sequence to Sequence Learning with Keras

Seq2seq Sequence to Sequence Learning with Keras Hi! You have just found Seq2Seq. Seq2Seq is a sequence to sequence learning add-on for the python dee

Fariz Rahman 3.1k Dec 18, 2022
PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages

PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages Abstract NLP applications for code-mixed (CM) or mix-li

Mohsin Ali, Mohammed 1 Nov 12, 2021
Run Effective Large Batch Contrastive Learning on Limited Memory GPU

Gradient Cache Gradient Cache is a simple technique for unlimitedly scaling contrastive learning batch far beyond GPU memory constraint. This means tr

Luyu Gao 198 Dec 29, 2022
Fully Convolutional DenseNet (A.K.A 100 layer tiramisu) for semantic segmentation of images implemented in TensorFlow.

FC-DenseNet-Tensorflow This is a re-implementation of the 100 layer tiramisu, technically a fully convolutional DenseNet, in TensorFlow (Tiramisu). Th

Hasnain Raza 121 Oct 12, 2022
PyTorch implementation of popular datasets and models in remote sensing

PyTorch Remote Sensing (torchrs) (WIP) PyTorch implementation of popular datasets and models in remote sensing tasks (Change Detection, Image Super Re

isaac 222 Dec 28, 2022
A clean and extensible PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners

A clean and extensible PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners A PyTorch re-implementation of Mask Autoencoder trai

Tianyu Hua 23 Dec 13, 2022
Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.

Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.

Nerdy Rodent 2.3k Jan 04, 2023
Off-policy continuous control in PyTorch, with RDPG, RTD3 & RSAC

arXiv technical report soon available. we are updating the readme to be as comprehensive as possible Please ask any questions in Issues, thanks. Intro

Zhihan 31 Dec 30, 2022
Code for layerwise detection of linguistic anomaly paper (ACL 2021)

Layerwise Anomaly This repository contains the source code and data for our ACL 2021 paper: "How is BERT surprised? Layerwise detection of linguistic

6 Dec 07, 2022
Minimal But Practical Image Classifier Pipline Using Pytorch, Finetune on ResNet18, Got 99% Accuracy on Own Small Datasets.

PyTorch Image Classifier Updates As for many users request, I released a new version of standared pytorch immage classification example at here: http:

JinTian 106 Nov 06, 2022
Code for Talk-to-Edit (ICCV2021). Paper: Talk-to-Edit: Fine-Grained Facial Editing via Dialog.

Talk-to-Edit (ICCV2021) This repository contains the implementation of the following paper: Talk-to-Edit: Fine-Grained Facial Editing via Dialog Yumin

Yuming Jiang 221 Jan 07, 2023
Serving PyTorch 1.0 Models as a Web Server in C++

Serving PyTorch Models in C++ This repository contains various examples to perform inference using PyTorch C++ API. Run git clone https://github.com/W

Onur Kaplan 223 Jan 04, 2023
Human Pose estimation with TensorFlow framework

Human Pose Estimation with TensorFlow Here you can find the implementation of the Human Body Pose Estimation algorithm, presented in the DeeperCut and

Eldar Insafutdinov 1.1k Dec 29, 2022
An end-to-end project on customer segmentation

End-to-end Customer Segmentation Project Note: This project is in progress. Tools Used in This Project Prefect: Orchestrate workflows hydra: Manage co

Ocelot Consulting 8 Oct 06, 2022
PyTorch implementations of the paper: "DR.VIC: Decomposition and Reasoning for Video Individual Counting, CVPR, 2022"

DRNet for Video Indvidual Counting (CVPR 2022) Introduction This is the official PyTorch implementation of paper: DR.VIC: Decomposition and Reasoning

tao han 35 Nov 22, 2022
🛰️ List of earth observation companies and job sites

Earth Observation Companies & Jobs source Portals & Jobs Geospatial Geospatial jobs newsletter: ~biweekly newsletter with geospatial jobs by Ali Ahmad

Dahn 64 Dec 27, 2022
CompilerGym is a library of easy to use and performant reinforcement learning environments for compiler tasks

CompilerGym is a library of easy to use and performant reinforcement learning environments for compiler tasks

Facebook Research 721 Jan 03, 2023
Lucid Sonic Dreams syncs GAN-generated visuals to music.

Lucid Sonic Dreams Lucid Sonic Dreams syncs GAN-generated visuals to music. By default, it uses NVLabs StyleGAN2, with pre-trained models lifted from

731 Jan 02, 2023
Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance

Nested Graph Neural Networks About Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance.

Muhan Zhang 38 Jan 05, 2023
TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network

TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network Created by Seunghoon Hong, Junhyuk Oh,

42 Jun 29, 2022