DORS: Dynamic Attention Routing for Diffusion-based Object Removal in Dense Scenes
Object removal aims to eliminate target objects specified by a mask while preserving visual consistency with the surrounding regions. Existing methods typically rely on contextual information from surrounding regions. However, in dense scenes where the surrounding regions contain instances visually similar to the removal target, such reliance often leads to semantic interference, resulting in incomplete removal. This problem arises from erroneous information propagation in the attention space, where masked queries tend to align with such instances due to global similarity matching in self-attention. To address this challenge, we propose a Diffusion-based Object Removal framework for dense...
| Authors | Haitong Tang, Haipeng Liu, Yang Wang |
|---|---|
| Primary category | cs.CV |
| Published | 18 July 2026 |
| Last updated at source | 8 October 2026 |
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