BlobCtrl: A Unified and Flexible Framework for Element-level Image
  Generation and Editing
Element-level visual manipulation is essential in digital content creation,
but current diffusion-based methods lack the precision and flexibility of
traditional tools. In this work, we introduce BlobCtrl, a framework that
unifies element-level generation and editing using a probabilistic blob-based
representation. By employing blobs as visual primitives, our approach
effectively decouples and represents spatial location, semantic content, and
identity information, enabling precise element-level manipulation. Our key
contributions include: 1) a dual-branch diffusion architecture with
hierarchical feature fusion for seamless foreground-background integration; 2)
a self-supervised training paradigm with tailored data augmentation and score
functions; and 3) controllable dropout strategies to balance fidelity and
diversity. To support further research, we introduce BlobData for large-scale
training and BlobBench for systematic evaluation. Experiments show that
BlobCtrl excels in various element-level manipulation tasks while maintaining
computational efficiency, offering a practical solution for precise and
flexible visual content creation. Project page:
https://liyaowei-stu.github.io/project/BlobCtrl/
67d916b500030726e0df2a67
Yaowei Li
admin_assigned
2025-03-18T09:23:48.215Z
6362801380c1a705a6ea54ac
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Yaowei Li
user
Yw22
67d916b500030726e0df2a68
Lingen Li
admin_assigned
2025-03-18T09:23:54.498Z
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Lingen Li
user
l-li
67d916b500030726e0df2a69
Zhaoyang Zhang
claimed_verified
2025-03-18T08:07:22.583Z
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Zhaoyang Zhang
user
ZyZcuhk
67d916b500030726e0df2a6a
Xiaoyu Li
67d916b500030726e0df2a6b
Guangzhi Wang
admin_assigned
2025-03-18T09:24:18.787Z
6422b973ef9e8971003cdd22
/avatars/8564a2e984e2e79e46d90cc9c35e5773.svg
Guangzhi Wang
user
daoyuan98
67d916b500030726e0df2a6c
Hongxiang Li
admin_assigned
2025-03-18T09:24:25.700Z
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Hongxiang Li
user
HongxiangLi
67d916b500030726e0df2a6d
Xiaodong Cun
admin_assigned
2025-03-18T09:24:32.118Z
63184c517ca1b876d99b7e0e
https://cdn-avatars.huggingface.co/v1/production/uploads/63184c517ca1b876d99b7e0e/b-qDExoeJuDXK0cJBZKnz.jpeg
Xiaodong Cun
user
vinthony
67d916b500030726e0df2a6e
Ying Shan
admin_assigned
2025-03-18T09:24:39.725Z
63ca3ddc04c979828310bfcb
/avatars/615e0d8622950b4408b40d550f02a894.svg
Ying Shan
user
yshan2u
67d916b500030726e0df2a6f
Yuexian Zou
BlobCtrl: A Unified and Flexible Framework for Element-level Image
  Generation and Editing
Element-level visual manipulation is essential in digital content creation,
but current diffusion-based methods lack the precision and flexibility of
traditional tools. In this work, we introduce BlobCtrl, a framework that
unifies element-level generation and editing using a probabilistic blob-based
representation. By employing blobs as visual primitives, our approach
effectively decouples and represents spatial location, semantic content, and
identity information, enabling precise element-level manipulation. Our key
contributions include: 1) a dual-branch diffusion architecture with
hierarchical feature fusion for seamless foreground-background integration; 2)
a self-supervised training paradigm with tailored data augmentation and score
functions; and 3) controllable dropout strategies to balance fidelity and
diversity. To support further research, we introduce BlobData for large-scale
training and BlobBench for systematic evaluation. Experiments show that
BlobCtrl excels in various element-level manipulation tasks while maintaining
computational efficiency, offering a practical solution for precise and
flexible visual content creation. Project page:
https://liyaowei-stu.github.io/project/BlobCtrl/
BlobCtrl is a framework that uses a probabilistic blob-based representation for element-level generation and editing, offering precision and flexibility through a dual-branch diffusion architecture, self-supervised training, and controllable dropout strategies.
diffusion-based methods probabilistic blob-based representation dual-branch diffusion architecture hierarchical feature fusion foreground-background integration self-supervised training tailored data augmentation score functions controllable dropout strategies BlobData BlobBench