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arXiv Computer Vision By Silin Cheng, Yang Liu, Xinwei He, Sebastien Ourselin, Lei Tan, Gen Luo

WeakMCN: Multi-task Collaborative Network for Weakly Supervised Referring Expression Comprehension and Segmentation

Read the original on arXiv Computer Vision →

WeakMCN introduces a multi-task collaborative network that jointly learns weakly supervised referring expression comprehension (WREC) and segmentation (WRES) using a dual-branch architecture. The WREC branch employs anchor-based contrastive learning and serves as a teacher for the WRES branch, while two novel modules—Dynamic Visual Feature Enhancement (DVFE) and Collaborative Consistency Module (CCM)—facilitate cross-task collaboration. Experiments on RefCOCO, RefCOCO+, and RefCOCOg show significant performance gains over single-task baselines, with up to 3.91% and 13.11% improvements on WREC and WRES respectively, and strong generalization in semi-supervised settings.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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