8 citations · 11 across the 16 of their papers we have counts for
11 papers · 1 filter
Beyond Pixels: From Video Priors to 4D Worlds
Zihao Liu, Xiaolong Shen, Zhenglin Zhou +2
4D generation synthesizes dynamic 3D scenes from conditions such as text or images. Existing methods either reconstruct generated RGB videos with a separate 4D model or adapt a par…
SpecLoR: Spectral Lookahead Rectification for Motion-Coherent Text-to-Video Generation
Xu Zhang, Yu Lu, Ruijie Quan +3
Flow Matching has enabled robust text-to-video generation via latent ODE sampling. However, velocity approximation and numerical discretization errors inevitably accumulate, causin…
ITS3D: Inference-Time Scaling for Text-Guided 3D Diffusion Models
Zhenglin Zhou, Fan Ma, Xiaobo Xia +3
We explore inference-time scaling in text-guided 3D diffusion models to enhance generative quality without additional training. To this end, we introduce ITS3D, a framework that fo…
AnchorFlow: Training-Free 3D Editing via Latent Anchor-Aligned Flows
Zhenglin Zhou, Fan Ma, Chengzhuo Gui +4
Training-free 3D editing aims to modify 3D shapes based on human instructions without model finetuning. It plays a crucial role in 3D content creation. However, existing approaches…
Adversarial-Guided Diffusion for Multimodal LLM Attacks
Chengwei Xia, Fan Ma, Ruijie Quan +2
This paper addresses the challenge of generating adversarial image using a diffusion model to deceive multimodal large language models (MLLMs) into generating the targeted response…
Insert Anything: Image Insertion via In-Context Editing in DiT
Wensong Song, Hong Jiang, Zongxing Yang +2
This work presents Insert Anything, a unified framework for reference-based image insertion that seamlessly integrates objects from reference images into target scenes under flexib…
BrainGuard: Privacy-Preserving Multisubject Image Reconstructions from Brain Activities
Zhibo Tian, Ruijie Quan, Fan Ma +2
Reconstructing perceived images from human brain activity forms a crucial link between human and machine learning through Brain-Computer Interfaces. Early methods primarily focused…
Autonomous LLM-Enhanced Adversarial Attack for Text-to-Motion
Honglei Miao, Fan Ma, Ruijie Quan +2
Human motion generation driven by deep generative models has enabled compelling applications, but the ability of text-to-motion (T2M) models to produce realistic motions from text…
VividDreamer: Invariant Score Distillation For Hyper-Realistic Text-to-3D Generation
Wenjie Zhuo, Fan Ma, Hehe Fan +1
This paper presents Invariant Score Distillation (ISD), a novel method for high-fidelity text-to-3D generation. ISD aims to tackle the over-saturation and over-smoothing problems i…
Psychometry: An Omnifit Model for Image Reconstruction from Human Brain Activity
Ruijie Quan, Wenguan Wang, Zhibo Tian +2
Reconstructing the viewed images from human brain activity bridges human and computer vision through the Brain-Computer Interface. The inherent variability in brain function betwee…
HeadStudio: Text to Animatable Head Avatars with 3D Gaussian Splatting
Zhenglin Zhou, Fan Ma, Hehe Fan +2
Creating digital avatars from textual prompts has long been a desirable yet challenging task. Despite the promising results achieved with 2D diffusion priors, current methods strug…