2026-10-13T04:25:25Z https://www.scidb.cn/oai

10.57760/sciencedb.013bv 2026-09-23T11:03:41Z

2026-09-23 Source Code for DepthCut: Interactive Segmentation with Depth Guidance for Complex Scenarios doi:10.57760/sciencedb.013bv en This repository provides the source code accompanying the paper “DepthCut: Interactive Segmentation with Depth Guidance for Complex Scenarios.” DepthCut is a depth-guided interactive image segmentation framework that integrates RGB appearance features and depth-based geometric features through an Adaptive Gated Context Fusion module. It aims to improve segmentation in challenging scenarios, including camouflage, underwater scenes, and low-light conditions. The released code documents the implementation of the proposed method and supports related research and reproduction efforts. This release contains source code and accompanying documentation only; it does not include original image datasets, experimental result data, or pretrained model weights. Interactive image segmentation; Depth guidance; Camouflaged Objec Weishuo Yuan PUBLIC https://api.github.com/licenses/mit dataset Science Data Bank