Implicit Warping for Animation with Image Sets
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Abstract (arXiv)
We present a new implicit warping framework for image animation using sets of source images through the transfer of the motion of a driving video. A single cross- modal attention layer is used to find correspondences between the source images and the driving image, choose the most appropriate features from different source images, and warp the selected features. This is in contrast to the existing methods that use explicit flow-based warping, which is designed for animation using a single source and does not extend well to multiple sources. The pick-and-choose capability of our framework helps it achieve state-of-the-art results on multiple datasets for image animation using both single and multiple source images. The project website is available at https://deepimagination.cc/implicit warping/
Key facts. Cited by 45 papers in the map (data through 7 Oct 2026). Builds on 46 of its 54 references that are in the map. First posted on arXiv 4 Oct 2022.
Builds on
46 of 54 references.
References · 46
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Citing papers per year: 2022: 3; 2023: 11; 2024: 14; 2025: 14; 2026: 3.
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- 2026Leveraging Avatar Fingerprinting: A Multi-Generator Photorealistic Talking-Head Public Database and Benchmark27 Mar 2026
- 2026DISPLAY: Directable Human-Object Interaction Video Generation via Sparse Motion Guidance and Multi-Task Auxiliary10 Mar 2026
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- 2025SynergyWarpNet: Attention-Guided Cooperative Warping for Neural Portrait Animation19 Dec 2025
- 2025Instant Expressive Gaussian Head Avatars at Over 100 FPS18 Dec 2025
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- 2025X-NeMo: Expressive Neural Motion Reenactment via Disentangled Latent Attention30 Jul 2025
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- 2024Superior and Pragmatic Talking Face Generation with Teacher-Student Framework26 Mar 2024
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- 2023DreamPose: Fashion Image-to-Video Synthesis via Stable Diffusion12 Apr 2023
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- 2022SPACE: Speech-driven Portrait Animation with Controllable Expressioncited by 49
- 2025X-NeMo: Expressive Neural Motion Reenactment via Disentangled Latent Attentioncited by 26
- 2023Unsupervised Volumetric Animationcited by 18
12 most cited of 37 All 37 (JSON)
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12 newest of 37 All 37 (JSON)