1 citations · 2 across the 13 of their papers we have counts for
17 papers
REEL: Learning to Retrieve, Evaluate, and Evolve Visual Memory for Any Long-Horizon Multi-Shot Video Generation
Hang Xu, Guohui Zhang, Xiaoxiao Ma +7
Memory-based long-video generation aims to combine user control with long-range visual consistency. We organize this process into three functional components: a planner, an adapter…
Where Does the Watermark Hide? Push-Pull Disentanglement for Invisible Watermark Removal
Jidong Yang, Huaike Yu, Qi Li +4
Fixed image distortions do not cover an attacker that learns from paired clean and watermarked images. We study this paired-training threat with single-image inference: deployment…
RemTraceNet: Few-Shot Forensic Detection of Invisible Watermark Attacks
Jidong Yang, Huaike Yu, Qi Li +6
Removing an invisible watermark and concealing the forensic evidence are distinct objectives: successfully disrupting the embedded watermark does not imply that the removal process…
Disentangle and Drop: Robust Universal Removal of Image Watermarks via Reconstructive Grayscale Residual Decomposition
Qi Li, Jidong Yang, Feng-Lei Fan +7
Invisible image watermarks are commonly evaluated against benign postprocessing operations such as compression, resizing, blur, and color changes. These tests leave out a different…
Style as Cover: Deep Image Steganography via Stylized Transmission
Qi Li, Jidong Yang, Huaike Yu +6
Image steganography hides secret message within normal images, with most existing works relying on cover-preserving transmission. However, such a paradigm becomes vulnerable once t…
One Prompt Is Enough: Watermark Laundering Through Foundation Image Models
Jidong Yang, Qi Li, Wei Zong +5
Invisible watermarks are typically evaluated against predefined perturbations such as compression, blur, noise, cropping, and denoising. Public foundation image models expose a dis…
AnchorEdit: Maintaining Temporal Consistency in Multi-turn Image Editing via Causal Memory
Hang Xu, Xiaoxiao Ma, Guohui Zhang +7
Multi-turn image editing is essential for iterative design, yet current models often struggle with identity drift and error accumulation over successive steps. While existing resea…
OmniNFT: Modality-wise Omni Diffusion Reinforcement for Joint Audio-Video Generation
Guohui Zhang, XiaoXiao Ma, Jie Huang +9
Recent advances in joint audio-video generation have been remarkable, yet real-world applications demand strong per-modality fidelity, cross-modal alignment, and fine-grained synch…
RAE-AR: Taming Autoregressive Models with Representation Autoencoders
Hu Yu, Hang Xu, Jie Huang +4
The latent space of generative modeling is long dominated by the VAE encoder. The latents from the pretrained representation encoders (e.g., DINO, SigLIP, MAE) are previously consi…
MaskFocus: Focusing Policy Optimization on Critical Steps for Masked Image Generation
Guohui Zhang, Hu Yu, Xiaoxiao Ma +3
Reinforcement learning (RL) has demonstrated significant potential for post-training language models and autoregressive visual generative models, but adapting RL to masked generati…
Towards Better & Faster Autoregressive Image Generation: From the Perspective of Entropy
Xiaoxiao Ma, Feng Zhao, Pengyang Ling +6
In this work, we first revisit the sampling issues in current autoregressive (AR) image generation models and identify that image tokens, unlike text tokens, exhibit lower informat…
Group Critical-token Policy Optimization for Autoregressive Image Generation
Guohui Zhang, Hu Yu, Xiaoxiao Ma +6
Recent studies have extended Reinforcement Learning with Verifiable Rewards (RLVR) to autoregressive (AR) visual generation and achieved promising progress. However, existing metho…
SynBoost: A Synergistic Framework for Fast Sampling of Diffusion Models
Hu Yu, Hao Luo, Xueyang Fu +3
Diffusion probabilistic models (DPMs) have demonstrated remarkable success in visual generation. However, their iterative sampling mechanism results in slow inference speeds. While…
FreePCA: Integrating Consistency Information across Long-short Frames in Training-free Long Video Generation via Principal Component Analysis
Jiangtong Tan, Hu Yu, Jie Huang +2
Long video generation involves generating extended videos using models trained on short videos, suffering from distribution shifts due to varying frame counts. It necessitates the…
Frequency Autoregressive Image Generation with Continuous Tokens
Hu Yu, Hao Luo, Hangjie Yuan +3
Autoregressive (AR) models for image generation typically adopt a two-stage paradigm of vector quantization and raster-scan ``next-token prediction", inspired by its great success…
DiffLoss: unleashing diffusion model as constraint for training image restoration network
Jiangtong Tan, Feng Zhao
Image restoration aims to enhance low quality images, producing high quality images that exhibit natural visual characteristics and fine semantic attributes. Recently, the diffusio…
FreqMamba: Viewing Mamba from a Frequency Perspective for Image Deraining
Zou Zhen, Yu Hu, Zhao Feng
Images corrupted by rain streaks often lose vital frequency information for perception, and image deraining aims to solve this issue which relies on global and local degradation mo…