AnyI2V: Animating Any Conditional Image with Motion Control
Ziye Li, Hao Luo, Xincheng Shuai, Henghui Ding
2025年份
2被引次数
4顶会引用
摘要
Recent advancements in video generation, particularly in diffusion models, have driven notable progress in text-tovideo (T2V) and image-to-video (I2V) synthesis. However, challenges remain in effectively integrating dynamic motion signals and flexible spatial constraints. Existing T2V methods typically rely on text prompts, which inherently lack precise control over the spatial layout of generated content.
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引用它的顶会 Paper4
- SceneDesigner: Controllable Multi-Object Image Generation with 9-DoF Pose ManipulationZhenyuan Qin, Xincheng Shuai, Henghui DingNeurIPS 2025 · 被引用 11 次
- GlyphPrinter: Region-Grouped Direct Preference Optimization for Glyph-Accurate Visual Text RenderingXincheng Shuai, Ziye Li, Henghui Ding, Dacheng TaoCVPR 2026 · 被引用 4 次
- PSDesigner: Automated Graphic Design with a Human-Like Creative WorkflowXincheng Shuai, Song Tang, Yutong Huang, Henghui Ding 等CVPR 2026 · 被引用 1 次
- OcclusionFormer: Arranging Z-Order for Layout-Grounded Image GenerationZiye Li, Henghui DingICML 2026
它引用的顶会 Paper31
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- Video Diffusion ModelsJonathan Ho, Tim Salimans, Alexey A. Gritsenko, William Chan 等NeurIPS 2022 · 被引用 2,948 次
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