Code for ACM MM 2020 paper "NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination"

Overview

NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination

The offical implementation for the "NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination" which is published in ACM MM 2020.

We propose Nearby Objects Hallucinator (NOH), which pinpoints the objects nearby each proposal with a Gaussian distribution, together with NOH-NMS, which dynamically eases the suppression for the space that might contain other objects with a high likelihood.

This work has won the first place at the CrowdHuman Challenge, 2020.

Performance

Model Backbone AP Recall MR Weights
Faster RCNN ResNet-50 85.0 87.5 44.5 faster_rcnn_model_final.pth
NOH-NMS ResNet-50 88.8 92.6 43.7 noh_nms_model_final.pth

Prepare Datasets

Download the CrowdHuman Datasets from http://www.crowdhuman.org/, and then move them under the directory like:

./data/crowdhuman
├── annotations
│   └── annotation_train.odgt
│   └── annotation_val.odgt
├── images
│   └── train
│   └── val

Installation

  cd detectron2
  pip install -e . 
  #or rebuild
  sh build.sh

Quick Start

See GETTING_STARTED.md in detectron2

Acknowledgement

Citation

if you find this project useful for your research, please cite:

@inproceedings{zhou2020noh,
  title={NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination},
  author={Zhou, Penghao and Zhou, Chong and Peng, Pai and Du, Junlong and Sun, Xing and Guo, Xiaowei and Huang, Feiyue},
  booktitle={Proceedings of the 28th ACM International Conference on Multimedia},
  pages={1967--1975},
  year={2020}
}
Owner
Tencent YouTu Research
Tencent YouTu Research
This repository contains the code to replicate the analysis from the paper "Moving On - Investigating Inventors' Ethnic Origins Using Supervised Learning"

Replication Code for 'Moving On' - Investigating Inventors' Ethnic Origins Using Supervised Learning This repository contains the code to replicate th

Matthias Niggli 0 Jan 04, 2022
An open-access benchmark and toolbox for electricity price forecasting

epftoolbox The epftoolbox is the first open-access library for driving research in electricity price forecasting. Its main goal is to make available a

97 Dec 05, 2022
Repository for the semantic WMI loss

Installation: pip install -e . Installing DL2: First clone DL2 in a separate directory and install it using the following commands: git clone https:/

Nick Hoernle 4 Sep 15, 2022
[ICCV2021] Official code for "Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition"

CTR-GCN This repo is the official implementation for Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition. The pap

Yuxin Chen 148 Dec 16, 2022
Official implementation of "Articulation Aware Canonical Surface Mapping"

Articulation-Aware Canonical Surface Mapping Nilesh Kulkarni, Abhinav Gupta, David F. Fouhey, Shubham Tulsiani Paper Project Page Requirements Python

Nilesh Kulkarni 56 Dec 16, 2022
Code Repository for Liquid Time-Constant Networks (LTCs)

Liquid time-constant Networks (LTCs) [Update] A Pytorch version is added in our sister repository: https://github.com/mlech26l/keras-ncp This is the o

Ramin Hasani 553 Dec 27, 2022
This is a repository for a Semantic Segmentation inference API using the Gluoncv CV toolkit

BMW Semantic Segmentation GPU/CPU Inference API This is a repository for a Semantic Segmentation inference API using the Gluoncv CV toolkit. The train

BMW TechOffice MUNICH 56 Nov 24, 2022
FIRA: Fine-Grained Graph-Based Code Change Representation for Automated Commit Message Generation

FIRA is a learning-based commit message generation approach, which first represents code changes via fine-grained graphs and then learns to generate commit messages automatically.

Van 21 Dec 30, 2022
Image Super-Resolution by Neural Texture Transfer

SRNTT: Image Super-Resolution by Neural Texture Transfer Tensorflow implementation of the paper Image Super-Resolution by Neural Texture Transfer acce

Zhifei Zhang 413 Nov 30, 2022
DeepMind Alchemy task environment: a meta-reinforcement learning benchmark

The DeepMind Alchemy environment is a meta-reinforcement learning benchmark that presents tasks sampled from a task distribution with deep underlying structure.

DeepMind 188 Dec 25, 2022
A copy of Ares that costs 30 fucking dollars.

Finalement, j'ai décidé d'abandonner cette idée, je me suis comporté comme un enfant qui été en colère. Comme m'ont dit certaines personnes j'ai des c

Bleu 24 Apr 14, 2022
A program that can analyze videos according to the weights you select

MaskMonitor A program that can analyze videos according to the weights you select 下載 訓練完的 weight檔案 執行 MaskDetection.py 內部可更改 輸入來源(鏡頭, 影片, 圖片) 以及輸出條件(人

Patrick_star 1 Nov 07, 2021
3D HourGlass Networks for Human Pose Estimation Through Videos

3D-HourGlass-Network 3D CNN Based Hourglass Network for Human Pose Estimation (3D Human Pose) from videos. This was my summer'18 research project. Dis

Naman Jain 51 Jan 02, 2023
Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.

VQGAN-CLIP-GENERATOR Overview This is a package (with available notebook) for running VQGAN+CLIP locally, with a focus on ease of use, good documentat

Ryan Hamilton 98 Dec 30, 2022
The repo contains the code to train and evaluate a system which extracts relations and explanations from dialogue.

The repo contains the code to train and evaluate a system which extracts relations and explanations from dialogue. How do I cite D-REX? For now, cite

Alon Albalak 6 Mar 31, 2022
StyleGAN-Human: A Data-Centric Odyssey of Human Generation

StyleGAN-Human: A Data-Centric Odyssey of Human Generation Abstract: Unconditional human image generation is an important task in vision and graphics,

stylegan-human 762 Jan 08, 2023
ArtEmis: Affective Language for Art

ArtEmis: Affective Language for Art Created by Panos Achlioptas, Maks Ovsjanikov, Kilichbek Haydarov, Mohamed Elhoseiny, Leonidas J. Guibas Introducti

Panos 268 Dec 12, 2022
An implementation of the proximal policy optimization algorithm

PPO Pytorch C++ This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment t

Martin Huber 59 Dec 09, 2022
Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning

CSRL Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning Python: 3

4 Apr 14, 2022
CUDA Python Low-level Bindings

CUDA Python Low-level Bindings

NVIDIA Corporation 529 Jan 03, 2023