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arXiv · 2604.14630

CMTM: Cross-Modal Token Modulation for Unsupervised Video Object Segmentation

Inseok Jeon·Suhwan Cho·Minhyeok Lee·Seunghoon Lee·Minseok Kang·Jungho Lee·Chaewon Park·Donghyeong Kim·Sangyoun Lee
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Abstract

Recent advances in unsupervised video object segmentation have highlighted the potential of two-stream architectures that integrate appearance and motion cues. However, fully leveraging these complementary sources of information requires effectively modeling their interdependencies. In this paper, we introduce cross-modality token modulation, a novel approach designed to strengthen the interaction between appearance and motion cues. Our method establishes dense connections between tokens from each modality, enabling efficient intra-modal and inter-modal information propagation through relation transformer blocks. To improve learning efficiency, we incorporate a token masking strategy that addresses the limitations of relying solely on increased model complexity. Our approach achieves state-of-the-art performance across all public benchmarks, outperforming existing methods.

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Inseok Jeon, Suhwan Cho, Minhyeok Lee, Seunghoon Lee, Minseok Kang, Jungho Lee, Chaewon Park, Donghyeong Kim, Sangyoun Lee. 2026-04-16. CMTM: Cross-Modal Token Modulation for Unsupervised Video Object Segmentation. https://arxiv.org/abs/2604.14630

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