activity
20232026
most citedV2A-Mark: Versatile Deep Visual-Audio Watermarking for Manipulation Localization and Copyright Protection

2 citations · 7 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2026

UniVOE: A Removal-Driven Framework for Interaction-Aware Universal Video Object Editing

Shuzhou Yang, Lanqing Guo, Lingen Li +4

Video object removal and injection are reciprocal editing operations between object-present and object-absent video states, yet they differ substantially in training difficulty. Re…

cs.CV2026

DualDiff3D: Dual Structure-Appearance Diffusion Priors for Reliability-Enhanced 3D Gaussian Splatting

Qian Wang, Yu Wang, Weiqi Li +4

While 3D Gaussian Splatting (3DGS) has revolutionized 3D reconstruction and novel-view synthesis, scenarios with limited input views often lead to poor reconstruction quality and a…

cs.CV2024★ 1 cited

ReVideo: Remake a Video with Motion and Content Control

Chong Mou, Mingdeng Cao, Xintao Wang +3

Despite significant advancements in video generation and editing using diffusion models, achieving accurate and localized video editing remains a substantial challenge. Additionall…

cs.CV2024★ 1 cited

Diffusion-Based Hierarchical Image Steganography

Youmin Xu, Xuanyu Zhang, Jiwen Yu +3

This paper introduces Hierarchical Image Steganography, a novel method that enhances the security and capacity of embedding multiple images into a single container using diffusion…

cs.CV2024★ 2 cited

V2A-Mark: Versatile Deep Visual-Audio Watermarking for Manipulation Localization and Copyright Protection

Xuanyu Zhang, Youmin Xu, Runyi Li +4

AI-generated video has revolutionized short video production, filmmaking, and personalized media, making video local editing an essential tool. However, this progress also blurs th…

cs.CV2024★ 1 cited

Invertible Diffusion Models for Compressed Sensing

Bin Chen, Zhenyu Zhang, Weiqi Li +5

While deep neural networks (NN) significantly advance image compressed sensing (CS) by improving reconstruction quality, the necessity of training current CS NNs from scratch const…

cs.CV2024

DiffEditor: Boosting Accuracy and Flexibility on Diffusion-based Image Editing

Chong Mou, Xintao Wang, Jiechong Song +2

Large-scale Text-to-Image (T2I) diffusion models have revolutionized image generation over the last few years. Although owning diverse and high-quality generation capabilities, tra…

cs.CV2023★ 1 cited

EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protection

Xuanyu Zhang, Runyi Li, Jiwen Yu +3

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 immin…

cs.CV2023★ 1 cited

AnimateZero: Video Diffusion Models are Zero-Shot Image Animators

Jiwen Yu, Xiaodong Cun, Chenyang Qi +4

Large-scale text-to-video (T2V) diffusion models have great progress in recent years in terms of visual quality, motion and temporal consistency. However, the generation process is…

cs.CV2023

Neural Video Fields Editing

Shuzhou Yang, Chong Mou, Jiwen Yu +3

Diffusion models have revolutionized text-driven video editing. However, applying these methods to real-world editing encounters two significant challenges: (1) the rapid increase…