QAHOI: Query-Based Anchors for Human-Object Interaction Detection (paper)

Related tags

Deep LearningQAHOI
Overview

QAHOI

QAHOI: Query-Based Anchors for Human-Object Interaction Detection (paper)

Requirements

  • PyTorch >= 1.5.1
  • torchvision >= 0.6.1
pip install -r requirements.txt
  • Compiling CUDA operators
cd ./models/ops
sh ./make.sh
# test
python test.py

Dataset Preparation

Please follow the HICO-DET dataset preparation of GGNet.

After preparation, the data folder as follows:

data
├── hico_20160224_det
|   ├── images
|   |   ├── test2015
|   |   └── train2015
|   └── annotations
|       ├── anno_list.json
|       ├── corre_hico.npy
|       ├── file_name_to_obj_cat.json
|       ├── hoi_id_to_num.json
|       ├── hoi_list_new.json
|       ├── test_hico.json
|       └── trainval_hico.json

Evaluation

Download the model to params folder.

  • We test the model with NVIDIA A6000 GPU, Pytorch 1.9.0, Python 3.8 and CUDA 11.2.
Model Full (def) Rare (def) None-Rare (def) Full (ko) Rare (ko) None-Rare (ko) Download
Swin-Tiny 28.47 22.44 30.27 30.99 24.83 32.84 model
Swin-Base*+ 33.58 25.86 35.88 35.34 27.24 37.76 model
Swin-Large*+ 35.78 29.80 37.56 37.59 31.36 39.36 model

Evaluating the model by running the following command.

--eval_extra to evaluate the spatio contribution.

mAP_default.json and mAP_ko.json will save in current folder.

  • Swin-Tiny
python main.py --resume params/QAHOI_swin_tiny_mul3.pth --backbone swin_tiny --num_feature_levels 3 --use_nms --eval
  • Swin-Base*+
python main.py --resume params/QAHOI_swin_base_384_22k_mul3.pth --backbone swin_base_384 --num_feature_levels 3 --use_nms --eval
  • Swin-Large*+
python main.py --resume params/QAHOI_swin_large_384_22k_mul3.pth --backbone swin_large_384 --num_feature_levels 3 --use_nms --eval

Training

Download the pre-trained swin-tiny model from Swin-Transformer to params folder.

Training QAHOI with Swin-Tiny from scratch.

python -m torch.distributed.launch \
        --nproc_per_node=8 \
        --use_env main.py \
        --backbone swin_tiny \
        --pretrained params/swin_tiny_patch4_window7_224.pth \
        --output_dir logs/swin_tiny_mul3 \
        --epochs 150 \
        --lr_drop 120 \
        --num_feature_levels 3 \
        --num_queries 300 \
        --use_nms

Training QAHOI with Swin-Base*+ from scratch.

python -m torch.distributed.launch \
        --nproc_per_node=8 \
        --use_env main.py \
        --backbone swin_base_384 \
        --pretrained params/swin_base_patch4_window7_224_22k.pth \
        --output_dir logs/swin_base_384_22k_mul3 \
        --epochs 150 \
        --lr_drop 120 \
        --num_feature_levels 3 \
        --num_queries 300 \
        --use_nms

Training QAHOI with Swin-Large*+ from scratch.

python -m torch.distributed.launch \
        --nproc_per_node=8 \
        --use_env main.py \
        --backbone swin_large_384 \
        --pretrained params/swin_large_patch4_window12_384_22k.pth \
        --output_dir logs/swin_large_384_22k_mul3 \
        --epochs 150 \
        --lr_drop 120 \
        --num_feature_levels 3 \
        --num_queries 300 \
        --use_nms

Citation

@article{cjw,
  title={QAHOI: Query-Based Anchors for Human-Object Interaction Detection},
  author={Junwen Chen and Keiji Yanai},
  journal={arXiv preprint arXiv:2112.08647},
  year={2021}
}
NeRF visualization library under construction

NeRF visualization library using PlenOctrees, under construction pip install nerfvis Docs will be at: https://nerfvis.readthedocs.org import nerfvis s

Alex Yu 196 Jan 04, 2023
Code for EMNLP2021 paper "Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training"

VoCapXLM Code for EMNLP2021 paper Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training Environment DockerFile: dancingso

Bo Zheng 15 Jul 28, 2022
PyTorch-based framework for Deep Hedging

PFHedge: Deep Hedging in PyTorch PFHedge is a PyTorch-based framework for Deep Hedging. PFHedge Documentation Neural Network Architecture for Efficien

139 Dec 30, 2022
Official PyTorch Code of GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection (CVPR 2021)

GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Mo

Abhinav Kumar 76 Jan 02, 2023
PyTorch implementation for our AAAI 2022 Paper "Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning"

deepGCFX PyTorch implementation for our AAAI 2022 Paper "Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning" Pr

Thilini Cooray 4 Aug 11, 2022
A plug-and-play library for neural networks written in Python

A plug-and-play library for neural networks written in Python!

Dimos Michailidis 2 Jul 16, 2022
[NAACL & ACL 2021] SapBERT: Self-alignment pretraining for BERT.

SapBERT: Self-alignment pretraining for BERT This repo holds code for the SapBERT model presented in our NAACL 2021 paper: Self-Alignment Pretraining

Cambridge Language Technology Lab 104 Dec 07, 2022
Project page of the paper 'Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network' (ECCVW 2018)

EPSR (Enhanced Perceptual Super-resolution Network) paper This repo provides the test code, pretrained models, and results on benchmark datasets of ou

Subeesh Vasu 78 Nov 19, 2022
Title: Graduate-Admissions-Predictor

The purpose of this project is create a predictive model capable of identifying the probability of a person securing an admit based on their personal profile parameters. Simplified visualisations hav

Akarsh Singh 1 Jan 26, 2022
MASS (Mueen's Algorithm for Similarity Search) - a python 2 and 3 compatible library used for searching time series sub-sequences under z-normalized Euclidean distance for similarity.

Introduction MASS allows you to search a time series for a subquery resulting in an array of distances. These array of distances enable you to identif

Matrix Profile Foundation 79 Dec 31, 2022
Python module providing a framework to trace individual edges in an image using Gaussian process regression.

Edge Tracing using Gaussian Process Regression Repository storing python module which implements a framework to trace individual edges in an image usi

Jamie Burke 7 Dec 27, 2022
CTC segmentation python package

CTC segmentation CTC segmentation can be used to find utterances alignments within large audio files. This repository contains the ctc-segmentation py

Ludwig Kürzinger 217 Jan 04, 2023
git git《Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking》(CVPR 2021) GitHub:git2] 《Masksembles for Uncertainty Estimation》(CVPR 2021) GitHub:git3]

Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking Ning Wang, Wengang Zhou, Jie Wang, and Houqiang Li Accepted by CVPR

NingWang 236 Dec 22, 2022
A nutritional label for food for thought.

Lexiscore As a first effort in tackling the theme of information overload in content consumption, I've been working on the lexiscore: a nutritional la

Paul Bricman 34 Nov 08, 2022
Group Fisher Pruning for Practical Network Compression(ICML2021)

Group Fisher Pruning for Practical Network Compression (ICML2021) By Liyang Liu*, Shilong Zhang*, Zhanghui Kuang, Jing-Hao Xue, Aojun Zhou, Xinjiang W

Shilong Zhang 129 Dec 13, 2022
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations

Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations Code repo for paper Trans-Encoder: Unsupervised sentence-pa

Amazon 101 Dec 29, 2022
GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)

GemNet: Universal Directional Graph Neural Networks for Molecules Reference implementation in PyTorch of the geometric message passing neural network

Data Analytics and Machine Learning Group 124 Dec 30, 2022
LBK 35 Dec 26, 2022
Code release for "Masked-attention Mask Transformer for Universal Image Segmentation"

Mask2Former: Masked-attention Mask Transformer for Universal Image Segmentation Bowen Cheng, Ishan Misra, Alexander G. Schwing, Alexander Kirillov, Ro

Meta Research 1.2k Jan 02, 2023
StorSeismic: An approach to pre-train a neural network to store seismic data features

StorSeismic: An approach to pre-train a neural network to store seismic data features This repository contains codes and resources to reproduce experi

Seismic Wave Analysis Group 11 Dec 05, 2022