7 citations · 12 across the 11 of their papers we have counts for
11 papers
Geometry-Aware Rotary Position Embedding for Consistent Video World Model
Chendong Xiang, Jiajun Liu, Jintao Zhang +7
Predictive world models that simulate future observations under explicit camera control are fundamental to interactive AI. Despite rapid advances, current systems lack spatial pers…
UniRef-Image-Edit: Towards Scalable and Consistent Multi-Reference Image Editing
Hongyang Wei, Bin Wen, Yancheng Long +22
We present UniRef-Image-Edit, a high-performance multi-modal generation system that unifies single-image editing and multi-image composition within a single framework. Existing dif…
Think-Then-Generate: Reasoning-Aware Text-to-Image Diffusion with LLM Encoders
Siqi Kou, Jiachun Jin, Zetong Zhou +8
Recent progress in text-to-image (T2I) diffusion models (DMs) has enabled high-quality visual synthesis from diverse textual prompts. Yet, most existing T2I DMs, even those equippe…
Focal Guidance: Unlocking Controllability from Semantic-Weak Layers in Video Diffusion Models
Yuanyang Yin, Yufan Deng, Shenghai Yuan +3
The task of Image-to-Video (I2V) generation aims to synthesize a video from a reference image and a text prompt. This requires diffusion models to reconcile high-frequency visual c…
Feature Partitioning and Semantic Equalization for Intrinsic Robustness in Semantic Communication under Packet Loss
Xiao Yang, Shuai Ma, Yong Liang +1
Semantic communication can improve transmission efficiency by focusing on task-relevant information. However, under packet-based communication protocols, any error typically result…
FeatureFool: Zero-Query Fooling of Video Models via Feature Map
Duoxun Tang, Xi Xiao, Guangwu Hu +6
The vulnerability of deep neural networks (DNNs) has been preliminarily verified. Existing black-box adversarial attacks usually require multi-round interaction with the model and…
MoMA: Multimodal LLM Adapter for Fast Personalized Image Generation
Kunpeng Song, Yizhe Zhu, Bingchen Liu +3
In this paper, we present MoMA: an open-vocabulary, training-free personalized image model that boasts flexible zero-shot capabilities. As foundational text-to-image models rapidly…
AnimateDiff-Lightning: Cross-Model Diffusion Distillation
Shanchuan Lin, Xiao Yang
We present AnimateDiff-Lightning for lightning-fast video generation. Our model uses progressive adversarial diffusion distillation to achieve new state-of-the-art in few-step vide…
SDXL-Lightning: Progressive Adversarial Diffusion Distillation
Shanchuan Lin, Anran Wang, Xiao Yang
We propose a diffusion distillation method that achieves new state-of-the-art in one-step/few-step 1024px text-to-image generation based on SDXL. Our method combines progressive an…
Diffusion Model with Perceptual Loss
Shanchuan Lin, Xiao Yang
Diffusion models without guidance generate very unrealistic samples. Guidance is used ubiquitously, and previous research has attributed its effect to low-temperature sampling that…
MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusion
Di Chang, Yichun Shi, Quankai Gao +7
In this work, we propose MagicPose, a diffusion-based model for 2D human pose and facial expression retargeting. Specifically, given a reference image, we aim to generate a person'…