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Matija Teršek's Projects

bayesian-crowd-counting icon bayesian-crowd-counting

Official Implement of ICCV 2019 oral paper Bayesian Loss for Crowd Count Estimation with Point Supervision

crowd-counting-scnn icon crowd-counting-scnn

This project is an implementation of the crowd counting model proposed in our CVPR 2017 paper - Switching Convolutional Neural Network(SCNN) for Crowd Counting. SCNN is an adaptation of the fully-convolutional neural network and uses an expert CNN that chooses the best crowd density CNN regressor for parts of the scene from a bag of regressors. This helps it tackle intra-scene crowd density variation and obtain SOTA results

csrnet-keras icon csrnet-keras

Implementation of the CSRNet paper (CVPR 18) in keras-tensorflow

csrnet-pytorch icon csrnet-pytorch

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

dm-count icon dm-count

Code for NeurIPS 2020 paper: Distribution Matching for Crowd Counting.

erk-2020 icon erk-2020

A review and comparison of time series similarity measures

ewasr icon ewasr

An embedded-compute-ready maritime obstacle detection network eWaSR.

lwcc icon lwcc

LWCC: A LightWeight Crowd Counting library for Python that includes several pretrained state-of-the-art models.

mediapipe icon mediapipe

Cross-platform, customizable ML solutions for live and streaming media.

mobileone icon mobileone

MobileOne - An Improved One millisecond Mobile Backbone. Unofficial Pytorch implementation for edge export - ONNX, OpenVINO.

mscnn icon mscnn

mscnn crowd counting model implementation, source from "Multi-scale Convolution Neural Networks for Crowd Counting" write by Zeng L, Xu X, Cai B, et al.

onnx icon onnx

Open standard for machine learning interoperability

realtimestereo icon realtimestereo

Attention-Aware Feature Aggregation for Real-time Stereo Matching on Edge Devices (ACCV, 2020)

sfanet-crowd-counting icon sfanet-crowd-counting

This is an unofficial implement of the arXiv paper Dual Path Multi-Scale Fusion Networks with Attention for Crowd Counting by PyTorch.

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