PED: DETR for Crowd Pedestrian Detection

Related tags

Deep LearningPED-DETR-for-Pedestrian-Detection
Overview

PED: DETR for Crowd Pedestrian Detection

License: MIT

Code for PED: DETR For (Crowd) Pedestrian Detection

Paper

PED: DETR for Crowd Pedestrian Detection

Installation

The codebases are built on top of Detectron2, DETR, Deformable DETR and Fast-Transformer

License

PED is released under MIT License.

Citing

If you use PED in your research, please consider citing:

@misc{lin2021detr,
      title={DETR for Crowd Pedestrian Detection}, 
      author={Matthieu Lin and Chuming Li and Xingyuan Bu and Ming Sun and Chen Lin and Junjie Yan and Wanli Ouyang and Zhidong Deng},
      year={2021},
      eprint={2012.06785},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}
Owner
lin matthieu
GitHub Repository
Contains code for the paper "Vision Transformers are Robust Learners".

Vision Transformers are Robust Learners This repository contains the code for the paper Vision Transformers are Robust Learners by Sayak Paul* and Pin

Sayak Paul 103 Jan 05, 2023
K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce (EMNLP Founding 2021)

Introduction K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce. Installation PyTor

Xu Song 21 Nov 16, 2022
Numerai tournament example scripts using NN and optuna

numerai_NN_example Numerai tournament example scripts using pytorch NN, lightGBM and optuna https://numer.ai/tournament Performance of my model based

Takahiro Maeda 12 Oct 10, 2022
Quick program made to generate alpha and delta tables for Hidden Markov Models

HMM_Calc Functions for generating Alpha and Delta tables from a Hidden Markov Model. Parameters: a: Matrix of transition probabilities. a[i][j] = a_{i

Adem Odza 1 Dec 04, 2021
Automatic Calibration for Non-repetitive Scanning Solid-State LiDAR and Camera Systems

ACSC Automatic extrinsic calibration for non-repetitive scanning solid-state LiDAR and camera systems. System Architecture 1. Dependency Tested with U

KINO 192 Dec 13, 2022
Codes and Data Processing Files for our paper.

Code Scripts and Processing Files for EEG Sleep Staging Paper 1. Folder Tree ./src_preprocess (data preprocessing files for SHHS and Sleep EDF) sleepE

Chaoqi Yang 18 Dec 12, 2022
[CVPR 2021] Pytorch implementation of Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs

Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs In this work, we propose a framework HijackGAN, which enables non-linear latent space travers

Hui-Po Wang 46 Sep 05, 2022
Revisiting Weakly Supervised Pre-Training of Visual Perception Models

SWAG: Supervised Weakly from hashtAGs This repository contains SWAG models from the paper Revisiting Weakly Supervised Pre-Training of Visual Percepti

Meta Research 134 Jan 05, 2023
Unofficial implementation of Fast-SCNN: Fast Semantic Segmentation Network

Fast-SCNN: Fast Semantic Segmentation Network Unofficial implementation of the model architecture of Fast-SCNN. Real-time Semantic Segmentation and mo

Philip Popien 69 Aug 11, 2022
This is an official implementation for "ResT: An Efficient Transformer for Visual Recognition".

ResT By Qing-Long Zhang and Yu-Bin Yang [State Key Laboratory for Novel Software Technology at Nanjing University] This repo is the official implement

zhql 222 Dec 13, 2022
SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning

SPCL SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning Update on 2021/11/25: ArXiv Ver

Binhui Xie (谢斌辉) 11 Oct 29, 2022
This repo is to present various code demos on how to use our Graph4NLP library.

Deep Learning on Graphs for Natural Language Processing Demo The repository contains code examples for DLG4NLP tutorials at NAACL 2021, SIGIR 2021, KD

Graph4AI 143 Dec 23, 2022
Zero-Cost Proxies for Lightweight NAS

Zero-Cost-NAS Companion code for the ICLR2021 paper: Zero-Cost Proxies for Lightweight NAS tl;dr A single minibatch of data is used to score neural ne

SamsungLabs 108 Dec 20, 2022
Head2Toe: Utilizing Intermediate Representations for Better OOD Generalization

Head2Toe: Utilizing Intermediate Representations for Better OOD Generalization Code for reproducing our results in the Head2Toe paper. Paper: arxiv.or

Google Research 62 Dec 12, 2022
Latent Network Models to Account for Noisy, Multiply-Reported Social Network Data

VIMuRe Latent Network Models to Account for Noisy, Multiply-Reported Social Network Data. If you use this code please cite this article (preprint). De

6 Dec 15, 2022
In this repo we reproduce and extend results of Learning in High Dimension Always Amounts to Extrapolation by Balestriero et al. 2021

In this repo we reproduce and extend results of Learning in High Dimension Always Amounts to Extrapolation by Balestriero et al. 2021. Balestriero et

Sean M. Hendryx 1 Jan 27, 2022
TF Image Segmentation: Image Segmentation framework

TF Image Segmentation: Image Segmentation framework The aim of the TF Image Segmentation framework is to provide/provide a simplified way for: Convert

Daniil Pakhomov 546 Dec 17, 2022
Automates Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning :rocket:

MLJAR Automated Machine Learning Documentation: https://supervised.mljar.com/ Source Code: https://github.com/mljar/mljar-supervised Table of Contents

MLJAR 2.4k Dec 31, 2022
CSD: Consistency-based Semi-supervised learning for object Detection

CSD: Consistency-based Semi-supervised learning for object Detection (NeurIPS 2019) By Jisoo Jeong, Seungeui Lee, Jee-soo Kim, Nojun Kwak Installation

80 Dec 15, 2022
A Fast and Accurate One-Stage Approach to Visual Grounding, ICCV 2019 (Oral)

One-Stage Visual Grounding ***** New: Our recent work on One-stage VG is available at ReSC.***** A Fast and Accurate One-Stage Approach to Visual Grou

Zhengyuan Yang 118 Dec 05, 2022