PED: DETR for Crowd Pedestrian Detection

Last update: Sep 13, 2022

Overview

PED: DETR for Crowd Pedestrian Detection

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

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PED: DETR for Crowd Pedestrian Detection

Related tags

Overview

PED: DETR for Crowd Pedestrian Detection

Paper

Installation

License

Citing

Owner

This initial strategy was developed specifically for larger pools and is based on taking a moving average and deriving Bollinger Bands to create a projected active liquidity range.

Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark dataset Office31.

Config files for my GitHub profile.

A Deep Learning Framework for Neural Derivative Hedging

Grammar Induction using a Template Tree Approach

Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation

Code for "Contextual Non-Local Alignment over Full-Scale Representation for Text-Based Person Search"

unofficial pytorch implement of "Squareplus: A Softplus-Like Algebraic Rectifier"

A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling"

Lowest memory consumption and second shortest runtime in NTIRE 2022 challenge on Efficient Super-Resolution

Code for the paper "Reinforcement Learning as One Big Sequence Modeling Problem"

[ACL 2022] LinkBERT: A Knowledgeable Language Model 😎 Pretrained with Document Links

Uses Open AI Gym environment to create autonomous cryptocurrency bot to trade cryptocurrencies.

Ppq - A powerful offline neural network quantization tool with custimized IR

Trying to understand alias-free-gan.

Various operations like path tracking, counting, etc by using yolov5

3D-Transformer: Molecular Representation with Transformer in 3D Space

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Code, environments, and scripts for the paper: "How Private Is Your RL Policy? An Inverse RL Based Analysis Framework"