Sponsorship
This workshop is for the 6th installment of the AI for Creative Visual Content Generation Editing and Understanding (CVEU), which follows its success on the previous launch at SIGGRAPAH'25, CVPR'24, ICCV'23, ECCV'22, ICCV'21, a Generative Models Course at SIGGRAPAH'24, 2023 Paris ShortFest AI Film Festival, and 2025 Hong Kong HKUST AI Film Festival.
It brings together researchers, artists and entrepreneurs working on computer graphics, human computer interaction, computer vision, machine learning, and cognitive research. It aims to bring awareness of recent advances in machine learning technologies to enable assisted creative visual content creation and understanding.
| Schedule | Nashville Time 2025-06-12 |
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| Warm-up Session | 12:45 PM - 1:10 PM |
| Workshop Opening Remarks | 1:10 PM - 1:15 PM |
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Session I - Future of Generative AI Research
• Keynote I - Ishan Misra • Keynote II - Matthias Niessner • Keynote III - Eli Shechtman • Roundtable Discussion (30 mins) |
1:15 PM - 3:00 PM |
| fal.ai - Generative Media in the Industry: How big is the wave? | 3:00 PM - 3:10 PM |
| Coffee Break / Poster Presentations | 3:10 PM - 3:45 PM |
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Session II - The Challenges of Generative Models in Practice
• Keynote I - Joel Simon • Keynote II - Dan B. Goldman • Keynote III - Nataniel Ruiz • Roundtable Discussion (30 mins) |
3:45 PM - 5:30 PM |
| Closing Remarks | 5:30 PM - 5:40 PM |
1. VerbDiff: Text-Only Diffusion Models with Enhanced Interaction Awareness
2. Unified Diffusion Transformer for Bidirectional Virtual Try-On and Try-Off
3. Wobble-Free 3D Talking Heads with Audio Driven Gaussian Splatting
4. Understanding Generative AI Capabilities in Everyday Image Editing Tasks
5. Instruction-Guided Precise Image Editing Using Multimodal LLMs
6. EditAnyScene: Text-Driven 3D Scene Local Editing with Gaussian Splatting
7. Personalized Text-to-Image Generation with Auto-Regressive Models
8. AIti-FAct: Content-Based Image Distortion for Synthetic Dataset Generation
9. Bring Anyone To Any Wall
Songlin Yang, Ziyi Wu, Ruihan Zhang, Diksha Meghwal, Shuai Yang, Mia Tang, Sean J. Liu, Tong Wu, Srinivasarao Daruna, Liwenhan Xie, Yuzhong Huang, Yi Wang, Gyeongsik Moon, Gaurav Parmar, Or Patashnik
| Track | Description | Important Dates (PST) |
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| In-proceeding Track |
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| Extended Abstract Track |
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| Invited Submission Track |
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The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2025 This workshop is for the 6th installment of the AI for Creative Visual Content Generation Editing and Understanding (CVEU). It brings together researchers working on computer vision, machine listening, computer graphics, human-computer interaction, and cognitive research. It aims to bring awareness of recent advances in machine learning technologies to enable assisted creative-video creation and understanding. The workshop will include invited talks by experts in the area and give the community opportunities to share their work via oral and poster presentations. We encourage practitioners, designers, students, post-docs, and researchers to submit work describing new ideas, work-in-progress, and previously or concurrently published research.
We accept full papers of up to 8 pages (excluding references) for in-proceeding track. All the submissions will go through a double-blind peer-review process with no rebuttal or second review cycle. Please submit your work to our CVEU OpenReview Console. Please use the CVPR template and follow CVPR 2025 Author Instruction. Authors of all accepted submissions will be asked to present their work in a poster session.
More details to come ...
