Soap2Soap uses a multi-agent system with dual-bridge consistency via JSON screenplays and visual anchors plus batch keyframe generation to achieve better long-term consistency in cinematic video remaking than commercial APIs.
Scail: Towards studio-grade character animation via in-context learning of 3d-consistent pose representations
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
fields
cs.CV 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
SCAIL-2 achieves end-to-end character animation via direct video concatenation, in-context mask conditioning, mode-specific RoPE, the synthetic MotionPair-60K dataset, and Bias-Aware DPO, outperforming prior methods on multiple tasks.
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.
citing papers explorer
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Soap2Soap: Long Cinematic Video Remaking via Multi-Agent Collaboration
Soap2Soap uses a multi-agent system with dual-bridge consistency via JSON screenplays and visual anchors plus batch keyframe generation to achieve better long-term consistency in cinematic video remaking than commercial APIs.
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SCAIL-2: Unifying Controlled Character Animation with End-to-end In-Context Conditioning
SCAIL-2 achieves end-to-end character animation via direct video concatenation, in-context mask conditioning, mode-specific RoPE, the synthetic MotionPair-60K dataset, and Bias-Aware DPO, outperforming prior methods on multiple tasks.
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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.