# Asymmetric Phase Coding Video Watermarking

arXiv: https://arxiv.org/abs/2608.29212 · HTML: https://mlsanity.com/paper/2608.29212/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 29 of its 46 references that are in the map.
- First posted on arXiv 29 Aug 2026.

## Builds on (most cited first, 29 of 29)

- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [HiDDeN: Hiding Data With Deep Networks](https://mlsanity.com/paper/1807.09937/) (2018)
- [The Stable Signature: Rooting Watermarks in Latent Diffusion Models](https://mlsanity.com/paper/2303.15435/) (2023)
- [Robust Invisible Video Watermarking with Attention](https://mlsanity.com/paper/1909.01285/) (2019)
- [Invisible Image Watermarks Are Provably Removable Using Generative AI](https://mlsanity.com/paper/2306.01953/) (2023)
- [MBRS : Enhancing Robustness of DNN-based Watermarking by Mini-Batch of Real and Simulated JPEG Compression](https://mlsanity.com/paper/2108.08211/) (2021)
- [Publicly-Detectable Watermarking for Language Models](https://mlsanity.com/paper/2310.18491/) (2023)
- [An Unforgeable Publicly Verifiable Watermark for Large Language Models](https://mlsanity.com/paper/2307.16230/) (2023)
- [SoK: Watermarking for AI-Generated Content](https://mlsanity.com/paper/2411.18479/) (2024)
- [Video Seal: Open and Efficient Video Watermarking](https://mlsanity.com/paper/2412.09492/) (2024)
- [AdaPool: Exponential Adaptive Pooling for Information-Retaining Downsampling](https://mlsanity.com/paper/2111.00772/) (2021)
- [DVMark: A Deep Multiscale Framework for Video Watermarking](https://mlsanity.com/paper/2104.12734/) (2021)
- [VideoShield: Regulating Diffusion-based Video Generation Models via Watermarking](https://mlsanity.com/paper/2501.14195/) (2025)
- [VideoMark: A Distortion-Free Robust Watermarking Framework for Video Diffusion Models](https://mlsanity.com/paper/2504.16359/) (2025)
- [Pixel Seal: Adversarial-only training for invisible image and video watermarking](https://mlsanity.com/paper/2512.16874/) (2025)
- [LVMark: Robust Watermark for Latent Video Diffusion Models](https://mlsanity.com/paper/2412.09122/) (2024)
- [On the Difficulty of Constructing a Robust and Publicly-Detectable Watermark](https://mlsanity.com/paper/2502.04901/) (2025)
- [ItoV: Efficiently Adapting Deep Learning-based Image Watermarking to Video Watermarking](https://mlsanity.com/paper/2305.02781/) (2023)
- [VideoMarkBench: Benchmarking Robustness of Video Watermarking](https://mlsanity.com/paper/2505.21620/) (2025)
- [Video Signature: Implicit Watermarking for Video Diffusion Models](https://mlsanity.com/paper/2506.00652/) (2025)
- [SPDMark: Selective Parameter Displacement for Robust Video Watermarking](https://mlsanity.com/paper/2512.12090/) (2025)
- [SIGMark: Scalable In-Generation Watermark with Blind Extraction for Video Diffusion](https://mlsanity.com/paper/2603.02882/) (2026)
- [Puppy: A Publicly Verifiable Watermarking Protocol](https://mlsanity.com/paper/2312.09125/) (2023)
- [DINVMark: A Deep Invertible Network for Video Watermarking](https://mlsanity.com/paper/2509.17416/) (2025)
- [FlowMark: Mask-Guided Video Watermarking](https://mlsanity.com/paper/2607.05261/) (2026)
- [Robust Video Watermarking against H.264 and H.265 Compression Attacks](https://mlsanity.com/paper/1708.02991/) (2017)
- [HEVC Watermarking Techniques for Authentication and Copyright Applications: Challenges and Opportunities](https://mlsanity.com/paper/2102.07195/) (2021)
- [VIDSTAMP: A Temporally-Aware Watermark for Ownership and Integrity in Video Diffusion Models](https://mlsanity.com/paper/2505.01406/) (2025)
- [PhaseMark: A Post-hoc, Optimization-Free Watermarking of AI-generated Images in the Latent Frequency Domain](https://mlsanity.com/paper/2601.13128/) (2026)

## Abstract (arXiv)

Existing video watermarking systems are symmetric: the party that can verify a mark holds the extractor weights or generator secret and can therefore also embed one. Benchmarks confirm the consequence, reporting that white-box forgery defeats all evaluated methods. We present a training-free video watermark that removes the shared secret. The signer embeds a complete Ed25519 signature into the phase spectrum of the chroma plane; any party holding the 32-byte public key and public per-video metadata verifies offline, with no model, no registry, and no network. The payload, 1024 bits of signed message with error correction, is an order of magnitude above common learned payloads and is carried by three design elements: a run-length temporal layout whose decoder identifies payload groups by correlation and never reads a frame index, a payload-free search that recovers scale, rotation, and translation from the carrier itself, and a closed-loop signing procedure that selects each video's embedding strength by self-verification through the unchanged public verifier. On 1000 uncurated real-world clips the system ships a verifying signature for 99.3% of the corpus and accepts a wrong public key zero times in 1000 attempts. An attack-aware acceptance gate yields embeddings that survive H.264 re-encoding at 100% and 50% rescaling at 97.4% on gated clips. The signature also verifies through a real display and capture loop, an axis absent from published evaluations.