FOMO: Forget the Concept, Don't Miss Out on the Scene in Selective Video Unlearning

arXiv:2609.39605 · cs.CV · Submitted 2026-09-30 · Read on arXiv

cs.CV

Submitted: 2026-09-30

Updated: 2026-09-30

Code: https://github.com/gmum/FOMO

Project page: https://gmum.github.io/FOMO

Terminology

• Diffusion Model — 15× in this paper · explained in 8 episodes
• Diffusion Models — 15× in this paper · explained in 6 episodes
• Transformer — 14× in this paper · explained in 2 episodes
• Consistency — 11× in this paper · explained in 3 episodes
• Benchmark — 9× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 5× in this paper
• Generative Model — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Generative Models — 4× in this paper · explained in 2 episodes
• Rectified Flow — 3× in this paper · explained in 3 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Adversarial Training — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Embeddings — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Frozen model — 1× in this paper · explained in 3 episodes
• Hypernetwork — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Joint Attention — 1× in this paper · explained in 2 episodes
• LoRA Adapters — 1× in this paper · explained in 3 episodes
• Machine Unlearning — 1× in this paper · explained in 2 episodes
• Steering — 1× in this paper · explained in 2 episodes

Sources

• Qwen3-VL Technical Report
• EraseAnything++: Enabling Concept Erasure in Rectified Flow Transformers Leveraging Multi-Object Optimization
• Unified Concept Editing in Diffusion Models
• Interpretable Motion-Attentive Maps: Spatio-Temporally Localizing Concepts in Video Diffusion Transformers
• HunyuanVideo: A Systematic Framework For Large Video Generative Models
• From Unlearning to UNBRANDING: A Benchmark for Trademark-Safe Text-to-Image Generation
• Wan: Open and Advanced Large-Scale Video Generative Models
• HarmVideoBench: Benchmarking Harmful Video Understanding in Large Multimodal Models
• Open-Sora: Democratizing Efficient Video Production for All

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