LensErase: A Foundation Model for Erase Anything
We introduce LensErase, a general-purpose mask-based Erase Anything foundation model designed to cover a broad spectrum of real-world erase scenarios.
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Key points
- LensErase supports diverse objects, visual text, watermarks, associated visual effects, multiple-object removal, and a wide range of object scales, aspect ratios, and image resolutions.
- First, to enable such broad coverage, we construct LensErase-100M, a large-scale dataset containing 101.07 million paired source-mask-target examples spanning diverse erase scenarios.
- Second, we pretrain LensErase from the text-to-image model Lens, adapting its strong generative prior to mask-based erasing.
- To efficiently incorporate the source image and erase mask, we propose Mask-Aware RoPE, a 3D rotary positional encoding that directly injects mask information into the source-image tokens without introducing a separate mask token sequence.
Sources (2)
- [1]LensErase: A Foundation Model for Erase AnythingarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 13, 09:56 AM
We introduce LensErase, a general-purpose mask-based Erase Anything foundation model designed to cover a broad spectrum of real-world erase scenarios.
LensErase supports diverse objects, visual text, watermarks, associated visual effects, multiple-object removal, and a wide range of object scales, aspect ratios, and image resolutions.
- [2]LensErase: A Foundation Model for Erase AnythingHugging Face Daily Papers · Oct 13, 09:56 AM · same content
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