Code and dataset for AAAI 2021 paper FixMyPose: Pose Correctional Describing and Retrieval Hyounghun Kim, Abhay Zala, Graham Burri, Mohit Bansal.

Overview

FixMyPose / फिक्समाइपोज़

Code and dataset for AAAI 2021 paper "FixMyPose: Pose Correctional Describing and Retrieval" Hyounghun Kim*, Abhay Zala*, Graham Burri, Mohit Bansal.

fixmypose-unc.github.io

Prerequisites

  • Python 3.6
  • PyTorch 1.4 or Up
  • For others packages, please run this command.
pip install -r requirements.txt

Dataset

Please download resized images from here and unzip in dataset/fixmypose folder.
Also, you can download full-sized images from here.

Usage

To train the models:

# pose correction describing model (English)
bash run.sh

# pose correction describing model (Hindi)
bash run_hindi.sh

# target pose retrieval model (English)
bash run_retrieval.sh

# target pose retrieval model (Hindi)
bash run_retrieval_hindi.sh

Task Specific Metric Usage

python body_part_match.py ./path/to/transform_files/ [FILES...]
python direction_match.py [FILES...]
python object_match.py [FILES...]

[FILES...] - list of files you wish to run the metric on (e.g. output_val_seen.json output_val_unseen.json output_test_unseen.json ...). The files will be created in the root directory when you finish evaluations.

Hindi METEOR Calculation

cd langeval/cococaption/pycocoevalcap/meteor
python meteor_hindi.py hindi_meteor.json

If you uncomment these two lines when evaluating, you can obtain the hindi_meteor.json file in the root folder.

Evaluation on Test split

Please contact [email protected] for the test split.

Acknowledgments

Base code is from "Expressing Visual Relationships via Language" paper's code repository.
Caption evaluation code is from Microsoft COCO Caption Evaluation.

Rainbow DQN implementation that outperforms the paper's results on 40% of games using 20x less data 🌈

Rainbow 🌈 An implementation of Rainbow DQN which reaches a median HNS of 205.7 after only 10M frames (the original Rainbow from Hessel et al. 2017 re

Dominik Schmidt 31 Dec 21, 2022
A CROSS-MODAL FUSION NETWORK BASED ON SELF-ATTENTION AND RESIDUAL STRUCTURE FOR MULTIMODAL EMOTION RECOGNITION

CFN-SR A CROSS-MODAL FUSION NETWORK BASED ON SELF-ATTENTION AND RESIDUAL STRUCTURE FOR MULTIMODAL EMOTION RECOGNITION The audio-video based multimodal

skeleton 15 Sep 26, 2022
Disagreement-Regularized Imitation Learning

Due to a normalization bug the expert trajectories have lower performance than the rl_baseline_zoo reported experts. Please see the following link in

Kianté Brantley 25 Apr 28, 2022
Text-Based Ideal Points

Text-Based Ideal Points Source code for the paper: Text-Based Ideal Points by Keyon Vafa, Suresh Naidu, and David Blei (ACL 2020). Update (June 29, 20

Keyon Vafa 37 Oct 09, 2022
A simple implementation of Kalman filter in Multi Object Tracking

kalman Filter in Multi-object Tracking A simple implementation of Kalman filter in Multi Object Tracking 本实现是在https://github.com/liuchangji/kalman-fil

124 Dec 29, 2022
Using fully convolutional networks for semantic segmentation with caffe for the cityscapes dataset

Using fully convolutional networks for semantic segmentation (Shelhamer et al.) with caffe for the cityscapes dataset How to get started Download the

Simon Guist 27 Jun 06, 2022
AI Virtual Calculator: This is a simple virtual calculator based on Artificial intelligence.

AI Virtual Calculator: This is a simple virtual calculator that works with gestures using OpenCV. We will use our hand in the air to click on the calc

Md. Rakibul Islam 1 Jan 13, 2022
Python library for tracking human heads with FLAME (a 3D morphable head model)

Video Head Tracker 3D tracking library for human heads based on FLAME (a 3D morphable head model). The tracking algorithm is inspired by face2face. It

61 Dec 25, 2022
Understanding Hyperdimensional Computing for Parallel Single-Pass Learning

Understanding Hyperdimensional Computing for Parallel Single-Pass Learning Authors: Tao Yu* Yichi Zhang* Zhiru Zhang Christopher De Sa *: Equal Contri

Cornell RelaxML 4 Sep 08, 2022
VLG-Net: Video-Language Graph Matching Networks for Video Grounding

VLG-Net: Video-Language Graph Matching Networks for Video Grounding Introduction Official repository for VLG-Net: Video-Language Graph Matching Networ

Mattia Soldan 25 Dec 04, 2022
PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers

CvT: Introducing Convolutions to Vision Transformers Pytorch implementation of CvT: Introducing Convolutions to Vision Transformers Usage: img = torch

Rishikesh (ऋषिकेश) 193 Jan 03, 2023
Text Extraction Formulation + Feedback Loop for state-of-the-art WSD (EMNLP 2021)

ConSeC is a novel approach to Word Sense Disambiguation (WSD), accepted at EMNLP 2021. It frames WSD as a text extraction task and features a feedback loop strategy that allows the disambiguation of

Sapienza NLP group 36 Dec 13, 2022
Adversarial Learning for Modeling Human Motion

Adversarial Learning for Modeling Human Motion This repository contains the open source code which reproduces the results for the paper: Adversarial l

wangqi 6 Jun 15, 2021
Object Tracking and Detection Using OpenCV

Object tracking is one such application of computer vision where an object is detected in a video, otherwise interpreted as a set of frames, and the object’s trajectory is estimated. For instance, yo

Happy N. Monday 4 Aug 21, 2022
PyTorch implementation of Octave Convolution with pre-trained Oct-ResNet and Oct-MobileNet models

octconv.pytorch PyTorch implementation of Octave Convolution in Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octa

Duo Li 273 Dec 18, 2022
learning and feeling SLAM together with hands-on-experiments

modern-slam-tutorial-python Learning and feeling SLAM together with hands-on-experiments 😀 😃 😆 Dependencies Most of the examples are based on GTSAM

Giseop Kim 59 Dec 22, 2022
Transformers based fully on MLPs

Awesome MLP-based Transformers papers An up-to-date list of Transformers based fully on MLPs without attention! Why this repo? After transformers and

Fawaz Sammani 35 Dec 30, 2022
Code to train models from "Paraphrastic Representations at Scale".

Paraphrastic Representations at Scale Code to train models from "Paraphrastic Representations at Scale". The code is written in Python 3.7 and require

John Wieting 71 Dec 19, 2022
git《Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser》(2021) GitHub: [fig5]

Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser Abstract The success of deep denoisers on real-world colo

Yue Cao 51 Nov 22, 2022
An algorithm study of the 6th iOS 10 set of Boost Camp Web Mobile

알고리즘 스터디 🔥 부스트캠프 웹모바일 6기 iOS 10조의 알고리즘 스터디 입니다. 개인적인 사정 등으로 S034, S055만 참가하였습니다. 스터디 목적 상진: 코테 합격 + 부캠끝나고 아침에 일어나기 위해 필요한 사이클 기완: 꾸준하게 자리에 앉아 공부하기 +

2 Jan 11, 2022