ManiVid: Unified and Explainable Forensic Analysis of Manipulated Videos

arXiv:2609.30934 · cs.CV · Submitted 2026-09-25 · Read on arXiv

cs.CV

Submitted: 2026-09-25

Updated: 2026-09-25

Terminology

• Grounding — 123× in this paper · explained in 3 episodes
• Accuracy — 33× in this paper · explained in 1 episode
• Ablation — 19× in this paper · explained in 1 episode
• Benchmark — 17× in this paper · explained in 2 episodes
• Consistency — 16× in this paper · explained in 3 episodes
• Embeddings — 13× in this paper · explained in 2 episodes
• Segmentation Masks — 13× in this paper · explained in 2 episodes
• Fidelity — 12× in this paper · explained in 2 episodes
• Verification — 12× in this paper · explained in 2 episodes
• Alignment — 11× in this paper · explained in 1 episode
• Forensic Evidence Router — 9× in this paper
• Prompt Distill Module — 9× in this paper
• Transformer — 9× in this paper · explained in 2 episodes
• Distillation — 8× in this paper · explained in 2 episodes
• CVF International Conference on Computer Vision — 6× in this paper
• Cosine Similarity — 6× in this paper · explained in 3 episodes
• Diffusion Model — 6× in this paper · explained in 8 episodes
• Aggregation — 5× in this paper · explained in 1 episode
• Cosine Similarity Score — 5× in this paper
• Over-smoothing — 5× in this paper · explained in 4 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• Trace — 5× in this paper · explained in 2 episodes
• Core — 4× in this paper · explained in 2 episodes
• Diffusion Models — 4× in this paper · explained in 6 episodes
• Ablation study — 3× in this paper · explained in 1 episode
• Adaptation — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 4 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 3 episodes
• Semantic Alignment — 2× in this paper · explained in 3 episodes
• Semantic Similarity — 2× in this paper · explained in 2 episodes
• Steering — 2× in this paper · explained in 2 episodes
• Temporal consistency — 2× in this paper · explained in 2 episodes
• Two-stage training — 2× in this paper · explained in 2 episodes
• Unified Framework — 2× in this paper · explained in 5 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Evaluation Dimensions — 1× in this paper · explained in 3 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Hallucination — 1× in this paper · explained in 4 episodes
• Homogeneity — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 9 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Two-Stage Training Strategy — 1× in this paper · explained in 3 episodes

Sources

• Qwen3-VL Technical Report
• Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
• The DeepFake Detection Challenge (DFDC) Dataset
• LTX-2: Efficient Joint Audio-Visual Foundation Model
• OpenVE-3M: A Large-Scale High-Quality Dataset for Instruction-Guided Video Editing
• CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers
• LoRA: Low-Rank Adaptation of Large Language Models
• So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection
• HunyuanVideo: A Systematic Framework For Large Video Generative Models
• Seeing Before Reasoning: A Unified Framework for Generalizable and Explainable Fake Image Detection
• FaceForensics: A Large-scale Video Dataset for Forgery Detection in Human Faces
• Kling-Omni Technical Report
• Wan: Open and Advanced Large-Scale Video Generative Models
• InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
• Qwen-Image Technical Report
• UltraVideo: High-Quality UHD Video Dataset with Comprehensive Captions
• VideoCoF: Unified Video Editing with Temporal Reasoner
• Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos
• On the Limitations of Cross-Lingual Consistency in Multilingual Text-to-image Generation
• FakeVLM-R1: Internalizing Physical Laws via CoT for Synthetic Image Detection

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