为了融入，首先解耦：通过上下文解耦表示重新思考伪装图像生成
To Blend In, First Decouple: Rethinking Camouflage Image Generation via Context-Decoupled Representations
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中文总结 AI 辅助
研究伪装图像生成问题，提出上下文解耦生成范式CamoDreamer，通过设计对比感知上下文桥等方法，将潜在伪装特征解耦为物体和背景控制流，实验证明其显著优于现有方法且设计轻量。
中文摘要 AI 辅助
伪装图像生成（CIG）专注于生成视觉上隐藏的物体，使其无缝融入背景。现有方法通常遵循背景引导范式或前景引导策略，但仍存在外观差异和背景伪影问题。我们将这些限制归因于跨上下文表示泄漏。为此，我们提出了一种新的上下文解耦生成范式CamoDreamer，旨在隔离上下文条件引导并将潜在伪装特征解耦为协调的物体和背景控制流。具体包括设计对比感知上下文桥、使用上下文解耦同化流、频率自适应上下文混合模块。实验表明CamoDreamer显著优于现有方法且设计相对轻量。
英文摘要
Camouflage image generation (CIG) focuses on generating visually concealed objects that seamlessly blend into their backgrounds. Existing methods typically follow either background-guided paradigms that adapt object appearance via style transfer, or foreground-guided strategies that outpaint surrounding regions conditioned on object features. However, they still suffer from appearance discrepancy and background artifacts. We attribute these limitations to cross-context representation leakage, where object and background cues are entangled in a coupled conditional space, resulting in ambiguous control and degraded camouflage fidelity. To tackle this, we propose a new context-decoupled generative paradigm, termed CamoDreamer, which aims to isolate contextual conditional guidance and explicitly decouple latent camouflage features into coordinated object and background control streams. First, a Contrast-aware Contextual Bridge is designed to model cross-context discrepancies and construct contrast-aware dual conditional guidance. Second, Context-Decoupled Assimilation Streams are employed to separate generative interactions conditioned on the dual guidance, while facilitating background rendering with target-aware cues in the latent space. Finally, a Frequency-Adaptive Contextual Blend module integrates complementary high-frequency textures and low-frequency structures from decoupled features to improve holistic coherence. Extensive experiments demonstrate that CamoDreamer consistently outperforms existing methods with a substantial margin, while maintaining a relatively lightweight design.
发表机构
- Beihang University（北京航空航天大学）
- Geely Automobile Research Institute (Ningbo) Co., Ltd（吉利汽车研究院（宁波）有限公司）
机构由 AI 辅助整理，请以论文原文为准。
