# Memory Aggregation Networks for Efficient Interactive Video Object Segmentation

Source: [Memory Aggregation Networks for Efficient Interactive Video Object Segmentation](<https://www.sota2.com/research/paper/68fa673d1e209131cea1520f>)

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

Data updated: 2025-12-25T07:44:51.478Z

Authors: Jiaxu Miao, Yunchao Wei, Yi Yang

Published: 2020-03-30T07:25:26.000Z

## Abstract

Interactive video object segmentation (iVOS) aims at efficiently harvesting high-quality segmentation masks of the target object in a video with user interactions. Most previous state-of-the-arts tackle the iVOS with two independent networks for conducting user interaction and temporal propagation, respectively, leading to inefficiencies during the inference stage. In this work, we propose a unified framework, named Memory Aggregation Networks (MA-Net), to address the challenging iVOS in a more efficient way. Our MA-Net integrates the interaction and the propagation operations into a single network, which significantly promotes the efficiency of iVOS in the scheme of multi-round interactions. More importantly, we propose a simple yet effective memory aggregation mechanism to record the informative knowledge from the previous interaction rounds, improving the robustness in discovering challenging objects of interest greatly. We conduct extensive experiments on the validation set of DAVIS Challenge 2018 benchmark. In particular, our MA-Net achieves the J@60 score of 76.1% without any bells and whistles, outperforming the state-of-the-arts with more than 2.7%.

## 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.

- [Interactive Video Object Segmentation on YouTube-IVOS (val)](<https://www.sota2.com/research/sota/interactive-video-object-segmentation-on-youtube-ivos-val.md>): Interactive Video Object Segmentation; YouTube-IVOS (val); J&F Score (1st Iteration): 0.525.

- [Interactive Video Object Segmentation on DAVIS 2017 (val)](<https://www.sota2.com/research/sota/interactive-video-object-segmentation-on-davis-2017-val.md>): Interactive Video Object Segmentation; DAVIS 2017 (val); AUC-J&F: 78.7.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2003.13246>)

[PDF](<https://arxiv.org/pdf/2003.13246.pdf>)