Cinematic Compositing Using Character-Environment-Harmonized Video Generation Models
Not on the map. Why?
Abstract (arXiv)
Cinematic compositing aims to integrate green-screen characters into novel environments while maintaining physical and photometric realism. Previous methods often fail to capture the complex bidirectional interactions between characters and their surroundings, which we characterize as Character-to-Environment (C2E) physical interaction and Environment-to-Character (E2C) lighting harmonization. To address this, we propose an end-to-end video diffusion framework that jointly models C2E and E2C interactions, specifically handling the challenges of interactive props. Our approach introduces a tri-mask-guided architecture with RGB-D joint denoising to ensure physically consistent interactions among the character, props, and environment. We further develop an efficient prior-driven data curation pipeline to construct high-quality relighting pairs without expensive rendering. Finally, a reference-conditioned mechanism enables controllable environment synthesis and precise prop replacement. Extensive experiments demonstrate that our framework significantly outperforms existing methods in cinematic-quality dynamic video compositing.
Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 43 of its 58 references that are in the map. First posted on arXiv 17 Jun 2026.
Builds on
43 of 58 references.
References · 43
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,588
- 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,231
- 2025Qwen3 Technical Reportcited by 8,510
- 2023BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Modelscited by 6,103
- 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,299
- 2024SAM 2: Segment Anything in Images and Videoscited by 2,820
- 2025Wan: Open and Advanced Large-Scale Video Generative Modelscited by 2,610
- 2021VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understandingcited by 600
- 2023InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generationcited by 492
- 2025VACE: All-in-One Video Creation and Editingcited by 473
- 2025Video Depth Anything: Consistent Depth Estimation for Super-Long Videoscited by 203
- 2024MimicMotion: High-Quality Human Motion Video Generation with Confidence-aware Pose Guidancecited by 198
31 more
- 2020Real-Time High-Resolution Background Mattingcited by 172
- 2021Robust High-Resolution Video Matting with Temporal Guidancecited by 137
- 2020Bridging Composite and Real: Towards End-to-end Deep Image Mattingcited by 89
- 2025VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Controlcited by 83
- 2023AVID: Any-Length Video Inpainting with Diffusion Modelcited by 81
- 2025Wan-Animate: Unified Character Animation and Replacement with Holistic Replicationcited by 79
- 2024Attentive Eraser: Unleashing Diffusion Model's Object Removal Potential via Self-Attention Redirection Guidancecited by 63
- 2025Animate Anyone 2: High-Fidelity Character Image Animation with Environment Affordancecited by 61
- 2023Relightful Harmonization: Lighting-aware Portrait Background Replacementcited by 57
- 2021Deep Video Matting via Spatio-Temporal Alignment and Aggregationcited by 41
- 2025Light-A-Video: Training-free Video Relighting via Progressive Light Fusioncited by 38
- 2025UniRelight: Learning Joint Decomposition and Synthesis for Video Relightingcited by 38
- 2025EX-4D: EXtreme Viewpoint 4D Video Synthesis via Depth Watertight Meshcited by 32
- 2025RelightVid: Temporal-Consistent Diffusion Model for Video Relightingcited by 28
- 2023Semi-supervised Parametric Real-world Image Harmonizationcited by 26
- 2025HOIGen-1M: A Large-scale Dataset for Human-Object Interaction Video Generationcited by 26
- 2025MatAnyone: Stable Video Matting with Consistent Memory Propagationcited by 24
- 2025UniLumos: Fast and Unified Image and Video Relighting with Physics-Plausible Feedbackcited by 12
- 2025Light-X: Generative 4D Video Rendering with Camera and Illumination Controlcited by 12
- 2025TC-Light: Temporally Coherent Generative Rendering for Realistic World Transfercited by 11
- 2024ActAnywhere: Subject-Aware Video Background Generationcited by 8
- 2025RelightMaster: Precise Video Relighting with Multi-plane Light Imagescited by 8
- 2025MatAnyone 2: Scaling Video Matting via a Learned Quality Evaluatorcited by 7
- 2025ByteLoom: Weaving Geometry-Consistent Human-Object Interactions through Progressive Curriculum Learningcited by 7
- 2025Beyond Static Scenes: Camera-controllable Background Generation for Human Motioncited by 6
- 2026MoCha:End-to-End Video Character Replacement without Structural Guidancecited by 6
- 2025FlowPortal: Residual-Corrected Flow for Training-Free Video Relighting and Background Replacementcited by 5
- 2026EditCtrl: Disentangled Local and Global Control for Real-Time Generative Video Editingcited by 5
- 2025ANYPORTAL: Zero-Shot Consistent Video Background Replacementcited by 4
- 2026LightCtrl: Training-free Controllable Video Relightingcited by 3
- 2026Relit-LiVE: Relight Video by Jointly Learning Environment Videocited by 1
Built on by
Not cited yet.
Similar, not cited
Close in wording, no citation either way
- 2026PAI-Actor: Cinematic Multi-Character Replacement in Dynamic Scenes
- 2024DreamCinema: Cinematic Transfer with Free Camera and 3D Character
- 2025Virtually Being: Customizing Camera-Controllable Video Diffusion Models with Multi-View Performance Captures
- 2025Yesnt: Are Diffusion Relighting Models Ready for Capture Stage Compositing? A Hybrid Alternative to Bridge the Gap
- 2026PAI-Studio: Cinematic Video Background Replacement with Camera-Aware Motion
- 2026HarmoVid: Relightful Video Portrait Harmonization
- 2026LightCrafter: PBR-Conditioned Video Diffusion Refinement for Controllable and Consistent Relighting
- 2026Generative Relightable Avatars