One-to-All Animation enables alignment-free character animation and image pose transfer via self-supervised outpainting reformulation, reference extraction, hybrid fusion attention, identity-robust pose control, and token replacement for long videos.
Dwnet: Dense warp-based network for pose-guided human video generation
4 Pith papers cite this work. Polarity classification is still indexing.
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EverAnimate restores drifted latent flow trajectories in chunked video generation via persistent latent propagation and restorative flow matching, achieving measurable gains in PSNR, SSIM, LPIPS, and FID over prior long-animation methods with only LoRA tuning.
LISA adds a likelihood-score alignment loss to the side branch of dual-branch controllable generators, accelerating convergence and improving results across image/video tasks with negligible extra cost.
Pose-dIVE augments Re-ID training sets with diffusion-generated images of diverse poses and viewpoints by conditioning on SMPL parameters.
citing papers explorer
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One-to-All Animation: Alignment-Free Character Animation and Image Pose Transfer
One-to-All Animation enables alignment-free character animation and image pose transfer via self-supervised outpainting reformulation, reference extraction, hybrid fusion attention, identity-robust pose control, and token replacement for long videos.
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EverAnimate: Minute-Scale Human Animation via Latent Flow Restoration
EverAnimate restores drifted latent flow trajectories in chunked video generation via persistent latent propagation and restorative flow matching, achieving measurable gains in PSNR, SSIM, LPIPS, and FID over prior long-animation methods with only LoRA tuning.
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LISA: Likelihood Score Alignment for Visual-condition Controllable Generation
LISA adds a likelihood-score alignment loss to the side branch of dual-branch controllable generators, accelerating convergence and improving results across image/video tasks with negligible extra cost.
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Pose-dIVE: Pose-Diversified Augmentation with Diffusion Model for Person Re-Identification
Pose-dIVE augments Re-ID training sets with diffusion-generated images of diverse poses and viewpoints by conditioning on SMPL parameters.