# MFSeg: Efficient Multi-frame 3D Semantic Segmentation

Source: [MFSeg: Efficient Multi-frame 3D Semantic Segmentation](<https://www.sota2.com/research/paper/68fa78641e209131cea782c1>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T06:52:53.434Z

Authors: Chengjie Huang, Krzysztof Czarnecki

Published: 2025-05-07T13:46:10.000Z

## Abstract

We propose MFSeg, an efficient multi-frame 3D semantic segmentation framework. By aggregating point cloud sequences at the feature level and regularizing the feature extraction and aggregation process, MFSeg reduces computational overhead while maintaining high accuracy. Moreover, by employing a lightweight MLP-based point decoder, our method eliminates the need to upsample redundant points from past frames. Experiments on the nuScenes and Waymo datasets show that MFSeg outperforms existing methods, demonstrating its effectiveness and efficiency.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2505.04408>)

[PDF](<https://arxiv.org/pdf/2505.04408.pdf>)