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
offical implement of our Lifelong Person Re-Identification via Adaptive Knowledge Accumulation in CVPR2021

LifelongReID Offical implementation of our Lifelong Person Re-Identification via Adaptive Knowledge Accumulation in CVPR2021 by Nan Pu, Wei Chen, Yu L

PeterPu 76 Dec 08, 2022
This repository contains the code for the ICCV 2019 paper "Occupancy Flow - 4D Reconstruction by Learning Particle Dynamics"

Occupancy Flow This repository contains the code for the project Occupancy Flow - 4D Reconstruction by Learning Particle Dynamics. You can find detail

189 Dec 29, 2022
这是一个yolox-pytorch的源码,可以用于训练自己的模型。

YOLOX:You Only Look Once目标检测模型在Pytorch当中的实现 目录 性能情况 Performance 实现的内容 Achievement 所需环境 Environment 小技巧的设置 TricksSet 文件下载 Download 训练步骤 How2train 预测步骤

Bubbliiiing 613 Jan 05, 2023
Repo for Photon-Starved Scene Inference using Single Photon Cameras, ICCV 2021

Photon-Starved Scene Inference using Single Photon Cameras ICCV 2021 Arxiv Project Video Bhavya Goyal, Mohit Gupta University of Wisconsin-Madison Abs

Bhavya Goyal 5 Nov 15, 2022
CVPR2021 Content-Aware GAN Compression

Content-Aware GAN Compression [ArXiv] Paper accepted to CVPR2021. @inproceedings{liu2021content, title = {Content-Aware GAN Compression}, auth

52 Nov 06, 2022
[CoRL 21'] TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo

TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo Lukas Koestler1*    Nan Yang1,2*,†    Niclas Zeller2,3    Daniel Cremers1

TUM Computer Vision Group 744 Jan 04, 2023
StyleGAN2-ada for practice

This version of the newest PyTorch-based StyleGAN2-ada is intended mostly for fellow artists, who rarely look at scientific metrics, but rather need a working creative tool. Tested on Python 3.7 + Py

vadim epstein 170 Nov 16, 2022
i3DMM: Deep Implicit 3D Morphable Model of Human Heads

i3DMM: Deep Implicit 3D Morphable Model of Human Heads CVPR 2021 (Oral) Arxiv | Poject Page This project is the official implementation our work, i3DM

Tarun Yenamandra 60 Jan 03, 2023
🚩🚩🚩

My CTF Challenges 2021 AIS3 Pre-exam / MyFirstCTF Name Category Keywords Difficulty ⒸⓄⓋⒾⒹ-①⑨ (MyFirstCTF Only) Reverse Baby ★ Piano Reverse C#, .NET ★

6 Oct 28, 2021
End-To-End Crowdsourcing

End-To-End Crowdsourcing Comparison of traditional crowdsourcing approaches to a state-of-the-art end-to-end crowdsourcing approach LTNet on sentiment

Andreas Koch 1 Mar 06, 2022
Interactive Image Segmentation via Backpropagating Refinement Scheme

Won-Dong Jang and Chang-Su Kim, Interactive Image Segmentation via Backpropagating Refinement Scheme, CVPR 2019

Won-Dong Jang 85 Sep 15, 2022
Deep Dual Consecutive Network for Human Pose Estimation (CVPR2021)

Beanie - is an asynchronous ODM for MongoDB, based on Motor and Pydantic. It uses an abstraction over Pydantic models and Motor collections to work wi

295 Dec 29, 2022
Code implementation for the paper 'Conditional Gaussian PAC-Bayes'.

CondGauss This repository contains PyTorch code for the paper Stochastic Gaussian PAC-Bayes. A novel PAC-Bayesian training method is implemented. Ther

0 Nov 01, 2021
Implement of "Training deep neural networks via direct loss minimization" in PyTorch for 0-1 loss

This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe

Cuong Nguyen 1 Jan 18, 2022
Implementation of ICCV21 paper: PnP-DETR: Towards Efficient Visual Analysis with Transformers

Implementation of ICCV 2021 paper: PnP-DETR: Towards Efficient Visual Analysis with Transformers arxiv This repository is based on detr Recently, DETR

twang 113 Dec 27, 2022
Building blocks for uncertainty-aware cycle consistency presented at NeurIPS'21.

UncertaintyAwareCycleConsistency This repository provides the building blocks and the API for the work presented in the NeurIPS'21 paper Robustness vi

EML Tübingen 19 Dec 12, 2022
CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images

CurriculumNet Introduction This repo contains related code and models from the ECCV 2018 CurriculumNet paper. CurriculumNet is a new training strategy

156 Jul 04, 2022
Vision-and-Language Navigation in Continuous Environments using Habitat

Vision-and-Language Navigation in Continuous Environments (VLN-CE) Project Website — VLN-CE Challenge — RxR-Habitat Challenge Official implementations

Jacob Krantz 132 Jan 02, 2023
Online-compatible Unsupervised Non-resonant Anomaly Detection Repository

Online-compatible Unsupervised Non-resonant Anomaly Detection Repository Repository containing all scripts used in the studies of Online-compatible Un

0 Nov 09, 2021
Efficient Sparse Attacks on Videos using Reinforcement Learning

EARL This repository provides a simple implementation of the work "Efficient Sparse Attacks on Videos using Reinforcement Learning" Example: Demo: Her

12 Dec 05, 2021