Ego-Forge: Text and Geometric-Attention Free Exo-to-Egocentric Video Generation

arXiv:2609.35368 · cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.CV

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/aigc-apps/VideoX-Fun

Terminology

• Diffusion Model — 12× in this paper · explained in 8 episodes
• Diffusion Models — 7× in this paper · explained in 6 episodes
• Adaptation — 4× in this paper · explained in 1 episode
• Reconstruction Error — 4× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Guided attention — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Distillation — 2× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Geometry-Guided Self-Attention — 2× in this paper
• Grounding — 2× in this paper · explained in 3 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Abstention — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Distribution Matching — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Wasserstein Distance — 1× in this paper · explained in 4 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• ReCamMaster: Camera-Controlled Generative Rendering from A Single Video
• Qwen3-VL Technical Report
• RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
• Project Aria: A New Tool for Egocentric Multi-Modal AI Research
• CameraCtrl: Enabling Camera Control for Text-to-Video Generation
• EgoExoBench: A Benchmark for First- and Third-person View Video Understanding in MLLMs
• ViPE: Video Pose Engine for 3D Geometric Perception
• OpenVLA: An Open-Source Vision-Language-Action Model
• Towards Comprehensive Scene Understanding: Integrating First and Third-Person Views for LVLMs
• Control Copy-Paste: Controllable Diffusion-Based Augmentation Method for Remote Sensing Few-Shot Object Detection
• Decoupled Weight Decay Regularization
• VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training
• Exo2EgoSyn: Unlocking Foundation Video Generation Models for Exocentric-to-Egocentric Video Synthesis
• R3M: A Universal Visual Representation for Robot Manipulation
• EarthSynth: Generating Informative Earth Observation with Diffusion Models
• EgoWorld: Translating Exocentric View to Egocentric View using Rich Exocentric Observations
• History-Guided Video Diffusion
• EgoExo-WM: Unlocking Exo Video for Ego World Models
• Wan: Open and Advanced Large-Scale Video Generative Models
• MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Details

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