Official implementation of paper "Query2Label: A Simple Transformer Way to Multi-Label Classification".

Overview

PWC PWC PWC PWC

Introdunction

This is the official implementation of the paper "Query2Label: A Simple Transformer Way to Multi-Label Classification".

Abstract

This paper presents a simple and effective approach to solving the multi-label classification problem. The proposed approach leverages Transformer decoders to query the existence of a class label. The use of Transformer is rooted in the need of extracting local discriminative features adaptively for different labels, which is a strongly desired property due to the existence of multiple objects in one image. The built-in cross-attention module in the Transformer decoder offers an effective way to use label embeddings as queries to probe and pool class-related features from a feature map computed by a vision backbone for subsequent binary classifications. Compared with prior works, the new framework is simple, using standard Transformers and vision backbones, and effective, consistently outperforming all previous works on five multi-label classification data sets, including MS-COCO, PASCAL VOC, NUS-WIDE, and Visual Genome. Particularly, we establish 91.3% mAP on MS-COCO. We hope its compact structure, simple implementation, and superior performance serve as a strong baseline for multi-label classification tasks and future studies.

fig

Results on MS-COCO:

fig

Quick start

  1. (optional) Star this repo.

  2. Clone this repo:

git clone [email protected]:SlongLiu/query2labels.git
cd query2labels
  1. Install cuda, PyTorch and torchvision.

Please make sure they are compatible. We test our models on two envs and other configs may also work:

cuda==11, torch==1.9.0, torchvision==0.10.0, python==3.7.3
or
cuda==10.2, torch==1.6.0, torchvision==0.7.0, python==3.7.3
  1. Install other needed packages.
pip install -r requirments.txt
  1. Data preparation.

Download MS-COCO 2014 and modify the path in lib/dataset/cocodataset.py: line 24, 25.

  1. Download pretrained models.

You could download pretrained models from this link. See more details below.

  1. Run!
python q2l_infer.py -a modelname --config /path/to/json/file --resume /path/to/pkl/file [other args]
e.g.
python q2l_infer.py -a 'Q2L-R101-448' --config "pretrained/Q2L-R101-448/config_new.json" -b 16 --resume 'pretrained/Q2L-R101-448/checkpoint.pkl'

pretrianed model

Modelname mAP link(Tsinghua-cloud)
Q2L-R101-448 84.9 this link
Q2L-R101-576 86.5 this link
Q2L-TResL-448 87.3 this link
Q2L-TResL_22k-448 89.2 this link
Q2L-SwinL-384 90.5 this link
Q2L-CvT_w24-384 91.3 this link

Training

Training scripts will be available later.

BibTex

@misc{liu2021query2label,
      title={Query2Label: A Simple Transformer Way to Multi-Label Classification}, 
      author={Shilong Liu and Lei Zhang and Xiao Yang and Hang Su and Jun Zhu},
      year={2021},
      eprint={2107.10834},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

Acknowledgement

We thank the authors of ASL, TResNet, detr, CvT, and Swin-Transformer for their great works and codes. Thanks to @mrT23 for sharing training tricks and providing a useful script for training.

Owner
Shilong Liu
A spicy chicken. www.lsl.zone
Shilong Liu
Improving Query Representations for DenseRetrieval with Pseudo Relevance Feedback:A Reproducibility Study.

APR The repo for the paper Improving Query Representations for DenseRetrieval with Pseudo Relevance Feedback:A Reproducibility Study. Environment setu

ielab 8 Nov 26, 2022
Python lib to talk to pylontech lithium batteries (US2000, US3000, ...) using RS485

python-pylontech Python lib to talk to pylontech lithium batteries (US2000, US3000, ...) using RS485 What is this lib ? This lib is meant to talk to P

Frank 26 Dec 28, 2022
CR-Fill: Generative Image Inpainting with Auxiliary Contextual Reconstruction. ICCV 2021

crfill Usage | Web App | | Paper | Supplementary Material | More results | code for paper ``CR-Fill: Generative Image Inpainting with Auxiliary Contex

182 Dec 20, 2022
OpenDelta - An Open-Source Framework for Paramter Efficient Tuning.

OpenDelta is a toolkit for parameter efficient methods (we dub it as delta tuning), by which users could flexibly assign (or add) a small amount parameters to update while keeping the most paramters

THUNLP 386 Dec 26, 2022
Simple data balancing baselines for worst-group-accuracy benchmarks.

BalancingGroups Code to replicate the experimental results from Simple data balancing baselines achieve competitive worst-group-accuracy. Replicating

Meta Research 29 Dec 02, 2022
Imagededup - 😎 Finding duplicate images made easy

imagededup is a python package that simplifies the task of finding exact and near duplicates in an image collection.

idealo 4.3k Jan 07, 2023
The PyTorch implementation of paper REST: Debiased Social Recommendation via Reconstructing Exposure Strategies

REST The PyTorch implementation of paper REST: Debiased Social Recommendation via Reconstructing Exposure Strategies. Usage Download dataset Download

DMIRLAB 2 Mar 13, 2022
This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

DropEdge: Towards Deep Graph Convolutional Networks on Node Classification This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Con

401 Dec 16, 2022
Genpass - A Passwors Generator App With Python3

Genpass Welcom again into another python3 App this is simply an Passwors Generat

Mal4D 1 Jan 09, 2022
Federated_learning codes used for the the paper "Evaluation of Federated Learning Aggregation Algorithms" and "A Federated Learning Aggregation Algorithm for Pervasive Computing: Evaluation and Comparison"

Federated Distance (FedDist) This is the code accompanying the Percom2021 paper "A Federated Learning Aggregation Algorithm for Pervasive Computing: E

GETALP 8 Jan 03, 2023
Very simple NCHW and NHWC conversion tool for ONNX. Change to the specified input order for each and every input OP. Also, change the channel order of RGB and BGR. Simple Channel Converter for ONNX.

scc4onnx Very simple NCHW and NHWC conversion tool for ONNX. Change to the specified input order for each and every input OP. Also, change the channel

Katsuya Hyodo 16 Dec 22, 2022
Learning Calibrated-Guidance for Object Detection in Aerial Images

Learning Calibrated-Guidance for Object Detection in Aerial Images arxiv We propose a simple yet effective Calibrated-Guidance (CG) scheme to enhance

51 Sep 22, 2022
Code for Mesh Convolution Using a Learned Kernel Basis

Mesh Convolution This repository contains the implementation (in PyTorch) of the paper FULLY CONVOLUTIONAL MESH AUTOENCODER USING EFFICIENT SPATIALLY

Yi_Zhou 35 Jan 03, 2023
Autonomous Movement from Simultaneous Localization and Mapping

Autonomous Movement from Simultaneous Localization and Mapping About us Built by a group of Clarkson University students with the help from Professor

14 Nov 07, 2022
Joint Versus Independent Multiview Hashing for Cross-View Retrieval[J] (IEEE TCYB 2021, PyTorch Code)

Thanks to the low storage cost and high query speed, cross-view hashing (CVH) has been successfully used for similarity search in multimedia retrieval. However, most existing CVH methods use all view

4 Nov 19, 2022
Make differentially private training of transformers easy for everyone

private-transformers This codebase facilitates fast experimentation of differentially private training of Hugging Face transformers. What is this? Why

Xuechen Li 73 Dec 28, 2022
Some toy examples of score matching algorithms written in PyTorch

toy_gradlogp This repo implements some toy examples of the following score matching algorithms in PyTorch: ssm-vr: sliced score matching with variance

Ending Hsiao 21 Dec 26, 2022
Learning kernels to maximize the power of MMD tests

Code for the paper "Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy" (arXiv:1611.04488; published at ICLR 2017), by Douga

Danica J. Sutherland 201 Dec 17, 2022
BC3407-Group-5-Project - BC3407 Group Project With Python

BC3407-Group-5-Project As the world struggles to contain the ever-changing varia

1 Jan 26, 2022
Implementing a simplified copy of Shazam application from scratch using MinHashing and LSH.

Building Shazam from scratch In this repository we tried to implement a simplified copy of the Shazam application able to tell you the name of a song

Arturo Ghinassi 0 Nov 17, 2022