9 citations · 13 across the 12 of their papers we have counts for
13 papers · 1 filter
SLARM: Streaming and Language-Aligned Reconstruction Model for Dynamic Scenes
Zhicheng Qiu, Jiarui Meng, Tong-an Luo +4
We propose SLARM, a feed-forward model that unifies dynamic scene reconstruction, semantic understanding, and real-time streaming inference. SLARM captures complex, non-uniform mot…
RobustSCI: Beyond Reconstruction to Restoration for Snapshot Compressive Imaging under Real-World Degradations
Hao Wang, Zhankuo Xu, Jiong Ni +3
Deep learning algorithms for video Snapshot Compressive Imaging (SCI) have achieved great success, yet they predominantly focus on reconstructing from clean measurements. This over…
Breaking the Vicious Cycle: Coherent 3D Gaussian Splatting from Sparse and Motion-Blurred Views
Zhankuo Xu, Chaoran Feng, Yingtao Li +5
3D Gaussian Splatting (3DGS) has emerged as a state-of-the-art method for novel view synthesis. However, its performance heavily relies on dense, high-quality input imagery, an ass…
Visual Persona: Foundation Model for Full-Body Human Customization
Jisu Nam, Soowon Son, Zhan Xu +6
We introduce Visual Persona, a foundation model for text-to-image full-body human customization that, given a single in-the-wild human image, generates diverse images of the indivi…
Video Motion Graphs
Haiyang Liu, Zhan Xu, Fa-Ting Hong +3
We present Video Motion Graphs, a system designed to generate realistic human motion videos. Using a reference video and conditional signals such as music or motion tags, the syste…
Generating, Fast and Slow: Scalable Parallel Video Generation with Video Interface Networks
Bhishma Dedhia, David Bourgin, Krishna Kumar Singh +5
Diffusion Transformers (DiTs) can generate short photorealistic videos, yet directly training and sampling longer videos with full attention across the video remains computationall…
RigAnything: Template-Free Autoregressive Rigging for Diverse 3D Assets
Isabella Liu, Zhan Xu, Wang Yifan +5
We present RigAnything, a novel autoregressive transformer-based model, which makes 3D assets rig-ready by probabilistically generating joints and skeleton topologies and assigning…
Free-viewpoint Human Animation with Pose-correlated Reference Selection
Fa-Ting Hong, Zhan Xu, Haiyang Liu +6
Diffusion-based human animation aims to animate a human character based on a source human image as well as driving signals such as a sequence of poses. Leveraging the generative ca…
Move-in-2D: 2D-Conditioned Human Motion Generation
Hsin-Ping Huang, Yang Zhou, Jui-Hsien Wang +4
Generating realistic human videos remains a challenging task, with the most effective methods currently relying on a human motion sequence as a control signal. Existing approaches…
Progressive Autoregressive Video Diffusion Models
Desai Xie, Zhan Xu, Yicong Hong +5
Current frontier video diffusion models have demonstrated remarkable results at generating high-quality videos. However, they can only generate short video clips, normally around 1…
NECA: Neural Customizable Human Avatar
Junjin Xiao, Qing Zhang, Zhan Xu +1
Human avatar has become a novel type of 3D asset with various applications. Ideally, a human avatar should be fully customizable to accommodate different settings and environments.…
ActAnywhere: Subject-Aware Video Background Generation
Boxiao Pan, Zhan Xu, Chun-Hao Paul Huang +4
Generating video background that tailors to foreground subject motion is an important problem for the movie industry and visual effects community. This task involves synthesizing b…
Template-Free Single-View 3D Human Digitalization with Diffusion-Guided LRM
Zhenzhen Weng, Jingyuan Liu, Hao Tan +4
Reconstructing 3D humans from a single image has been extensively investigated. However, existing approaches often fall short on capturing fine geometry and appearance details, hal…