SubjectAnchor: Subject-Aware Memory-to-Video for Multi-Shot Storytelling

arXiv:2609.34502 · cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.CV

Submitted: 2026-09-28

Updated: 2026-09-28

Terminology

• Consistency — 20× in this paper · explained in 3 episodes
• Transformer — 18× in this paper · explained in 2 episodes
• Alignment — 9× in this paper · explained in 1 episode
• Benchmark — 8× in this paper · explained in 2 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Diffusion Model — 5× in this paper · explained in 8 episodes
• Diffusion Models — 4× in this paper · explained in 6 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• Redundancy — 3× in this paper · explained in 2 episodes
• Time Series Forecasting — 3× in this paper · explained in 3 episodes
• IEEE International Conference on Multimedia and Expo — 2× in this paper
• Memory Augmentation — 2× in this paper · explained in 2 episodes
• Modularity — 2× in this paper · explained in 9 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Prompt Adherence — 1× in this paper · explained in 2 episodes
• Rectified Flow — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Self-distillation — 1× in this paper · explained in 6 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Two-Stage Training Strategy — 1× in this paper · explained in 3 episodes
• Two-stage training — 1× in this paper · explained in 2 episodes

Sources

• CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
• Cosmos World Foundation Model Platform for Physical AI
• Wan: Open and Advanced Large-Scale Video Generative Models
• PAI-Studio: Cinematic Video Background Replacement with Camera-Aware Motion
• StreamingEffect: Real-Time Human-Centric Video Effect Generation
• VISTA: Triplet-Supervised Video Style Transfer with Diffusion Transformers
• HunyuanVideo: A Systematic Framework For Large Video Generative Models
• Controllable Video Generation: A Survey
• A Survey on Long Video Generation: Challenges, Methods, and Prospects
• VGGRPO: Towards World-Consistent Video Generation with 4D Latent Reward
• SkyReels-A2: Compose Anything in Video Diffusion Transformers
• From Inpainting to Editing: Unlocking Robust Mask-Free Visual Dubbing via Generative Bootstrapping
• 3D-Aware Implicit Motion Control for View-Adaptive Human Video Generation
• HoloCine: Holistic Generation of Cinematic Multi-Shot Long Video Narratives
• ShoulderShot: Generating Over-the-Shoulder Dialogue Videos
• OneStory: Coherent Multi-Shot Video Generation with Adaptive Memory
• Helios: Real Real-Time Long Video Generation Model
• StoryMem: Multi-shot Long Video Storytelling with Memory
• CineTrans: Learning to Generate Videos with Cinematic Transitions via Masked Diffusion Models
• MoCha: Towards Movie-Grade Talking Character Synthesis

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models