Fine-Grained Urban Flow Inference

4 papers with code • 4 benchmarks • 2 datasets

Fine-grained urban flow inference (FUFI) aims to infer the fine-grained urban flow map from the coarse-grained one.

Most implemented papers

UrbanFM: Inferring Fine-Grained Urban Flows

yoshall/UrbanFM 6 Feb 2019

In this paper, we aim to infer the real-time and fine-grained crowd flows throughout a city based on coarse-grained observations.

Fine-Grained Urban Flow Inference

ouyangksoc/UrbanPy 5 Feb 2020

To tackle these issues, we develop a model entitled UrbanFM which consists of two major parts: 1) an inference network to generate fine-grained flow distributions from coarse-grained inputs that uses a feature extraction module and a novel distributional upsampling module; 2) a general fusion subnet to further boost the performance by considering the influence of different external factors.

Fine-grained Urban Flow Inference with Incomplete Data

2023-MindSpore-1/ms-code-100 IEEE Transactions on Knowledge and Data Engineering 2022

In this paper, we make the first attempt to infer fine-grained urban flows based on the incomplete coarse-grained urban flow observations, and propose a Multi-Task urban flow Completion and Super-Resolution network (MT-CSR for short) to simultaneously complete the coarse-grained urban flows and infer the fine-grained flows.

Spatial-Temporal Contrasting for Fine-Grained Urban Flow Inference

Xovee/stcf IEEE Transactions on Big Data 2023

Fine-grained urban flow inference (FUFI) problem aims to infer the fine-grained flow maps from coarse-grained ones, benefiting various smart-city applications by reducing electricity, maintenance, and operation costs.