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Found 10 papers, 5 papers with code
V2A-Mark: Versatile Deep Visual-Audio Watermarking for Manipulation Localization and Copyright Protection
Meanwhile, we introduce a sample-level audio localization method and a cross-modal copyright extraction mechanism to couple the information of audio and video frames.
Invertible Diffusion Models for Compressed Sensing
To enable such memory-intensive end-to-end finetuning, we propose a novel two-level invertible design to transform both (1) the multi-step sampling process and (2) the noise estimation U-Net in each step into invertible networks.
EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protection
In the era where AI-generated content (AIGC) models can produce stunning and lifelike images, the lingering shadow of unauthorized reproductions and malicious tampering poses imminent threats to copyright integrity and information security.
Neural Video Fields Editing
Specifically, we construct a neural video field, powered by tri-plane and sparse grid, to enable encoding long videos with hundreds of frames in a memory-efficient manner.
AnimateZero: Video Diffusion Models are Zero-Shot Image Animators
For appearance control, we borrow intermediate latents and their features from the text-to-image (T2I) generation for ensuring the generated first frame is equal to the given generated image.
DiffLLE: Diffusion-guided Domain Calibration for Unsupervised Low-light Image Enhancement
Specifically, we adopt a naive unsupervised enhancement algorithm to realize preliminary restoration and design two zero-shot plug-and-play modules based on diffusion model to improve generalization and effectiveness.
FreeDoM: Training-Free Energy-Guided Conditional Diffusion Model
In this work, we propose a training-Free conditional Diffusion Model (FreeDoM) used for various conditions.
Unlimited-Size Diffusion Restoration
Our simple, parameter-free approaches can be used not only for image restoration but also for image generation of unlimited sizes, with the potential to be a general tool for diffusion models.
Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model
Most existing Image Restoration (IR) models are task-specific, which can not be generalized to different degradation operators.
Ranked #1 on
Image Compressed Sensing
on CelebA
GAN Prior based Null-Space Learning for Consistent Super-Resolution
Consistency and realness have always been the two critical issues of image super-resolution.
