PostCam: Camera-Controllable Novel-View Video Generation with Query-Shared Cross-Attention

arXiv:2511.17185 · cs.CV · Submitted 2025-11-21 · Read on arXiv

cs.CV

Submitted: 2025-11-21

Updated: 2026-09-26

Terminology

• Accuracy — 26× in this paper · explained in 1 episode
• Query-Shared Cross-Attention — 22× in this paper
• Consistency — 21× in this paper · explained in 3 episodes
• Diffusion Model — 17× in this paper · explained in 8 episodes
• Transformer — 14× in this paper · explained in 2 episodes
• Fidelity — 13× in this paper · explained in 2 episodes
• Alignment — 11× in this paper · explained in 1 episode
• Two-stage training — 11× in this paper · explained in 2 episodes
• Diffusion Models — 10× in this paper · explained in 6 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Attention Mechanism — 7× in this paper · explained in 3 episodes
• Latent Space — 7× in this paper · explained in 7 episodes
• Cross-Attention Mechanism — 5× in this paper · explained in 2 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• Two-Stage Training Strategy — 5× in this paper · explained in 3 episodes
• Ablation study — 4× in this paper · explained in 1 episode
• Core — 4× in this paper · explained in 2 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Flow Matching — 3× in this paper · explained in 8 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 3 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Temporal consistency — 2× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Tokenization — 1× in this paper · explained in 2 episodes

Sources

• VD3D: Taming Large Video Diffusion Transformers for 3D Camera Control
• ReCamMaster: Camera-Controlled Generative Rendering from A Single Video
• GS-DiT: Advancing Video Generation with Pseudo 4D Gaussian Fields through Efficient Dense 3D Point Tracking
• Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
• Uni3C: Unifying Precisely 3D-Enhanced Camera and Human Motion Controls for Video Generation
• I2VControl-Camera: Precise Video Camera Control with Adjustable Motion Strength
• Diffusion as Shader: 3D-aware Video Diffusion for Versatile Video Generation Control
• AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
• CameraCtrl: Enabling Camera Control for Text-to-Video Generation
• CameraCtrl II: Dynamic Scene Exploration via Camera-controlled Video Diffusion Models
• Training-free Camera Control for Video Generation
• MotionMaster: Training-free Camera Motion Transfer For Video Generation
• HunyuanVideo: A Systematic Framework For Large Video Generative Models
• RealCam-I2V: Real-World Image-to-Video Generation with Interactive Complex Camera Control
• MotionClone: Training-Free Motion Cloning for Controllable Video Generation
• Flow Matching for Generative Modeling
• TrajectoryCrafter: Redirecting Camera Trajectory for Monocular Videos via Diffusion Models
• OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation
• CamCtrl3D: Single-Image Scene Exploration with Precise 3D Camera Control
• Make-A-Video: Text-to-Video Generation without Text-Video Data

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