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.
Processpainter: Learn painting process from sequence data
7 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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StreamingEffect enables real-time 720p human-centric video effect generation on one GPU via teacher-student distillation, keyframe control, and a new 130K video dataset.
PAI-Studio reformulates cinematic background replacement as in-context conditional generation inside a Diffusion Transformer with bidirectional attention, trained on a new 30K film-sourced dataset, and reports better motion consistency and relighting than prior open-source and commercial systems.
PaintCopilot models painting as an open-ended autoregressive process that predicts coherent brushstrokes from partial canvas observations using a ViT target predictor, flow-matching stroke generator, and VAE region sampler.
VISTA introduces a new synthetic triplet dataset and diffusion-transformer framework with style adapter that jointly models style, content, and motion to achieve state-of-the-art video style transfer.
OmniHumanoid factorizes transferable motion learning from embodiment-specific adaptation to enable scalable cross-embodiment video generation without paired data for new humanoids.
SandSim reconstructs temporally coherent sand painting processes from single images using curve-guided Gaussian splatting, subtractive compositing for accumulation, and semantic-guided stroke planning.
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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StreamingEffect: Real-Time Human-Centric Video Effect Generation
StreamingEffect enables real-time 720p human-centric video effect generation on one GPU via teacher-student distillation, keyframe control, and a new 130K video dataset.
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PAI-Studio: Cinematic Video Background Replacement with Camera-Aware Motion
PAI-Studio reformulates cinematic background replacement as in-context conditional generation inside a Diffusion Transformer with bidirectional attention, trained on a new 30K film-sourced dataset, and reports better motion consistency and relighting than prior open-source and commercial systems.
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PaintCopilot: Modeling Painting as Autonomous Artistic Continuation
PaintCopilot models painting as an open-ended autoregressive process that predicts coherent brushstrokes from partial canvas observations using a ViT target predictor, flow-matching stroke generator, and VAE region sampler.
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VISTA: Triplet-Supervised Video Style Transfer with Diffusion Transformers
VISTA introduces a new synthetic triplet dataset and diffusion-transformer framework with style adapter that jointly models style, content, and motion to achieve state-of-the-art video style transfer.
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OmniHumanoid: Streaming Cross-Embodiment Video Generation with Paired-Free Adaptation
OmniHumanoid factorizes transferable motion learning from embodiment-specific adaptation to enable scalable cross-embodiment video generation without paired data for new humanoids.
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SandSim: Curve-Guided Gaussian Splatting for Reconstructing Sand Painting Processes
SandSim reconstructs temporally coherent sand painting processes from single images using curve-guided Gaussian splatting, subtractive compositing for accumulation, and semantic-guided stroke planning.