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OmniXRef: A Unified Framework for Multimodal Multi-Reference Video Editing
Xiaoyan Cong, Tianyu Wang, Hyeonho Jeong +7
Creative intent in video editing can be expressed through text instructions (e.g., "remove the people"), image references (e.g., subject appearance), video references (e.g., camera…
FuseReg: Regularizing Layer Fusion Mitigates the Reconstruction-Generation Gap in Representation Autoencoders
Hongyang Du, Yunfei Xie, Junjie Ye +13
Representation autoencoders (RAEs) reuse features from a pretrained visual encoder as reconstruction and diffusion latents, integrating strong visual representations into image gen…
Ms. Forcing: Efficient Streaming Video Generation with Multi-Scale Patchification and Attention
Zekun Li, Xiaoyan Cong, Hongyu Li +5
Streaming video diffusion models have made substantial progress toward interactive and dynamic world simulation, but the nested autoregressive and denoising loops of conventional n…
UMO: Unified In-Context Learning Unlocks Motion Foundation Model Priors
Xiaoyan Cong, Zekun Li, Zhiyang Dou +9
Large-scale foundation models (LFMs) have recently made impressive progress in text-to-motion generation by learning strong generative priors from massive 3D human motion datasets…
PackUV: Packed Gaussian UV Maps for 4D Volumetric Video
Aashish Rai, Angela Xing, Anushka Agarwal +5
Volumetric videos offer immersive 4D experiences, but remain difficult to reconstruct, store, and stream at scale. Existing Gaussian Splatting based methods achieve high-quality re…
VideoGPA: Distilling Geometry Priors for 3D-Consistent Video Generation
Hongyang Du, Junjie Ye, Xiaoyan Cong +7
While recent video diffusion models (VDMs) produce visually impressive results, they fundamentally struggle to maintain 3D structural consistency, often resulting in object deforma…
VIVA: VLM-Guided Instruction-Based Video Editing with Reward Optimization
Xiaoyan Cong, Haotian Yang, Angtian Wang +4
Instruction-based video editing aims to modify an input video according to a natural-language instruction while preserving content fidelity and temporal coherence. However, existin…
GenHSI: Controllable Generation of Human-Scene Interaction Videos
Zekun Li, Rui Zhou, Rahul Sajnani +3
Large-scale pre-trained video diffusion models have exhibited remarkable capabilities in diverse video generation. However, existing solutions face several challenges in generating…
DyTact: Capturing Dynamic Contacts in Hand-Object Manipulation
Xiaoyan Cong, Angela Xing, Chandradeep Pokhariya +2
Reconstructing dynamic hand-object contacts is essential for realistic manipulation in AI character animation, XR, and robotics, yet it remains challenging due to heavy occlusions,…
Art3D: Training-Free 3D Generation from Flat-Colored Illustration
Xiaoyan Cong, Jiayi Shen, Zekun Li +3
Large-scale pre-trained image-to-3D generative models have exhibited remarkable capabilities in diverse shape generations. However, most of them struggle to synthesize plausible 3D…
Oscillation Inversion: Understand the structure of Large Flow Model through the Lens of Inversion Method
Yan Zheng, Zhenxiao Liang, Xiaoyan Cong +4
We explore the oscillatory behavior observed in inversion methods applied to large-scale text-to-image diffusion models, with a focus on the "Flux" model. By employing a fixed-poin…
4DRecons: 4D Neural Implicit Deformable Objects Reconstruction from a single RGB-D Camera with Geometrical and Topological Regularizations
Xiaoyan Cong, Haitao Yang, Liyan Chen +4
This paper presents a novel approach 4DRecons that takes a single camera RGB-D sequence of a dynamic subject as input and outputs a complete textured deforming 3D model over time.…
Automatic Controllable Colorization via Imagination
Xiaoyan Cong, Yue Wu, Qifeng Chen +1
We propose a framework for automatic colorization that allows for iterative editing and modifications. The core of our framework lies in an imagination module: by understanding the…