UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild Article Swipe
Can Qin
,
Shu Zhang
,
Ning Yu
,
Yihao Feng
,
Xinyi Yang
,
Yingbo Zhou
,
Huan Wang
,
Juan Carlos Niebles
,
Caiming Xiong
,
Silvio Savarese
,
Stefano Ermon
,
Yun Fu
,
Ran Xu
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2305.11147
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2305.11147
Achieving machine autonomy and human control often represent divergent objectives in the design of interactive AI systems. Visual generative foundation models such as Stable Diffusion show promise in navigating these goals, especially when prompted with arbitrary languages. However, they often fall short in generating images with spatial, structural, or geometric controls. The integration of such controls, which can accommodate various visual conditions in a single unified model, remains an unaddressed challenge. In response, we introduce UniControl, a new generative foundation model that consolidates a wide array of controllable condition-to-image (C2I) tasks within a singular framework, while still allowing for arbitrary language prompts. UniControl enables pixel-level-precise image generation, where visual conditions primarily influence the generated structures and language prompts guide the style and context. To equip UniControl with the capacity to handle diverse visual conditions, we augment pretrained text-to-image diffusion models and introduce a task-aware HyperNet to modulate the diffusion models, enabling the adaptation to different C2I tasks simultaneously. Trained on nine unique C2I tasks, UniControl demonstrates impressive zero-shot generation abilities with unseen visual conditions. Experimental results show that UniControl often surpasses the performance of single-task-controlled methods of comparable model sizes. This control versatility positions UniControl as a significant advancement in the realm of controllable visual generation.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2305.11147
- https://arxiv.org/pdf/2305.11147
- OA Status
- green
- Cited By
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4377164421
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4377164421Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2305.11147Digital Object Identifier
- Title
-
UniControl: A Unified Diffusion Model for Controllable Visual Generation In the WildWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-05-18Full publication date if available
- Authors
-
Can Qin, Shu Zhang, Ning Yu, Yihao Feng, Xinyi Yang, Yingbo Zhou, Huan Wang, Juan Carlos Niebles, Caiming Xiong, Silvio Savarese, Stefano Ermon, Yun Fu, Ran XuList of authors in order
- Landing page
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https://arxiv.org/abs/2305.11147Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2305.11147Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2305.11147Direct OA link when available
- Concepts
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Computer science, Context (archaeology), Task (project management), Artificial intelligence, Generative grammar, Adaptation (eye), Human–computer interaction, Computer vision, Engineering, Psychology, Biology, Systems engineering, Neuroscience, PaleontologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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24Total citation count in OpenAlex
- Citations by year (recent)
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2025: 10, 2024: 12, 2023: 2Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.images | 44 |
| abstract_inverted_index.model, | 66 |
| abstract_inverted_index.models | 20, 139 |
| abstract_inverted_index.single | 64 |
| abstract_inverted_index.sizes. | 189 |
| abstract_inverted_index.tasks, | 163 |
| abstract_inverted_index.unique | 161 |
| abstract_inverted_index.unseen | 171 |
| abstract_inverted_index.visual | 60, 108, 132, 172, 204 |
| abstract_inverted_index.within | 91 |
| abstract_inverted_index.Trained | 158 |
| abstract_inverted_index.augment | 135 |
| abstract_inverted_index.control | 5, 191 |
| abstract_inverted_index.diverse | 131 |
| abstract_inverted_index.enables | 103 |
| abstract_inverted_index.machine | 1 |
| abstract_inverted_index.methods | 185 |
| abstract_inverted_index.models, | 149 |
| abstract_inverted_index.promise | 26 |
| abstract_inverted_index.prompts | 117 |
| abstract_inverted_index.remains | 67 |
| abstract_inverted_index.results | 175 |
| abstract_inverted_index.unified | 65 |
| abstract_inverted_index.various | 59 |
| abstract_inverted_index.However, | 37 |
| abstract_inverted_index.HyperNet | 144 |
| abstract_inverted_index.allowing | 97 |
| abstract_inverted_index.autonomy | 2 |
| abstract_inverted_index.capacity | 128 |
| abstract_inverted_index.context. | 122 |
| abstract_inverted_index.enabling | 150 |
| abstract_inverted_index.language | 100, 116 |
| abstract_inverted_index.modulate | 146 |
| abstract_inverted_index.prompted | 33 |
| abstract_inverted_index.prompts. | 101 |
| abstract_inverted_index.singular | 93 |
| abstract_inverted_index.spatial, | 46 |
| abstract_inverted_index.systems. | 16 |
| abstract_inverted_index.Achieving | 0 |
| abstract_inverted_index.Diffusion | 24 |
| abstract_inverted_index.abilities | 169 |
| abstract_inverted_index.arbitrary | 35, 99 |
| abstract_inverted_index.controls, | 55 |
| abstract_inverted_index.controls. | 50 |
| abstract_inverted_index.different | 154 |
| abstract_inverted_index.diffusion | 138, 148 |
| abstract_inverted_index.divergent | 8 |
| abstract_inverted_index.generated | 113 |
| abstract_inverted_index.geometric | 49 |
| abstract_inverted_index.influence | 111 |
| abstract_inverted_index.introduce | 74, 141 |
| abstract_inverted_index.positions | 193 |
| abstract_inverted_index.primarily | 110 |
| abstract_inverted_index.represent | 7 |
| abstract_inverted_index.response, | 72 |
| abstract_inverted_index.surpasses | 180 |
| abstract_inverted_index.zero-shot | 167 |
| abstract_inverted_index.UniControl | 102, 125, 164, 178, 194 |
| abstract_inverted_index.adaptation | 152 |
| abstract_inverted_index.challenge. | 70 |
| abstract_inverted_index.comparable | 187 |
| abstract_inverted_index.conditions | 61, 109 |
| abstract_inverted_index.especially | 31 |
| abstract_inverted_index.foundation | 19, 79 |
| abstract_inverted_index.framework, | 94 |
| abstract_inverted_index.generating | 43 |
| abstract_inverted_index.generation | 168 |
| abstract_inverted_index.generative | 18, 78 |
| abstract_inverted_index.impressive | 166 |
| abstract_inverted_index.languages. | 36 |
| abstract_inverted_index.navigating | 28 |
| abstract_inverted_index.objectives | 9 |
| abstract_inverted_index.pretrained | 136 |
| abstract_inverted_index.structures | 114 |
| abstract_inverted_index.task-aware | 143 |
| abstract_inverted_index.UniControl, | 75 |
| abstract_inverted_index.accommodate | 58 |
| abstract_inverted_index.advancement | 198 |
| abstract_inverted_index.conditions, | 133 |
| abstract_inverted_index.conditions. | 173 |
| abstract_inverted_index.generation, | 106 |
| abstract_inverted_index.generation. | 205 |
| abstract_inverted_index.integration | 52 |
| abstract_inverted_index.interactive | 14 |
| abstract_inverted_index.performance | 182 |
| abstract_inverted_index.significant | 197 |
| abstract_inverted_index.structural, | 47 |
| abstract_inverted_index.unaddressed | 69 |
| abstract_inverted_index.versatility | 192 |
| abstract_inverted_index.Experimental | 174 |
| abstract_inverted_index.consolidates | 82 |
| abstract_inverted_index.controllable | 87, 203 |
| abstract_inverted_index.demonstrates | 165 |
| abstract_inverted_index.text-to-image | 137 |
| abstract_inverted_index.simultaneously. | 157 |
| abstract_inverted_index.condition-to-image | 88 |
| abstract_inverted_index.pixel-level-precise | 104 |
| abstract_inverted_index.single-task-controlled | 184 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 13 |
| citation_normalized_percentile |