95 citations · 267 across the 32 of their papers we have counts for
33 papers · 1 filter
Reasmory: 3D Reconstruction as Explicit Memory for VLMs Spatial Reasoning
Jixuan He, Xueting Li, Chieh Hubert Lin +1
Vision-Language Models (VLMs) exhibit emerging spatial reasoning capabilities, yet they remain unreliable on tasks requiring precise spatial understanding, such as viewpoint reason…
SOMA: Unifying Parametric Human Body Models
Jun Saito, Jiefeng Li, Michael de Ruyter +12
Parametric human body models are foundational to human reconstruction, animation, and simulation, yet they remain mutually incompatible: SMPL, SMPL-X, MHR, Anny, and related models…
ReCoSplat: Online Feed-Forward Gaussian Splatting via Render-and-Compare
Freeman Cheng, Botao Ye, Xueting Li +3
Online novel view synthesis requires a model to reconstruct a scene causally from a stream of observations while keeping it renderable at every moment. We present ReCoSplat, an onl…
Edit3r: Instant 3D Scene Editing from Sparse Unposed Images
Jiageng Liu, Weijie Lyu, Xueting Li +2
We present Edit3r, a feed-forward framework that reconstructs and edits 3D scenes in a single pass from unposed, view-inconsistent, instruction-edited images. Unlike prior methods…
Instant Expressive Gaussian Head Avatars at Over 100 FPS
Kaiwen Jiang, Xueting Li, Seonwook Park +3
Portrait animation has witnessed tremendous quality improvements thanks to recent advances in video diffusion models. However, these 2D methods often compromise 3D consistency and…
CoCo4D: Comprehensive and Complex 4D Scene Generation
Junwei Zhou, Xueting Li, Lu Qi +1
Existing 4D synthesis methods primarily focus on object-level generation or dynamic scene synthesis with limited novel views, restricting their ability to generate multi-view consi…
Synthesizing Consistent Novel Views via 3D Epipolar Attention without Re-Training
Botao Ye, Sifei Liu, Xueting Li +2
Large diffusion models demonstrate remarkable zero-shot capabilities in novel view synthesis from a single image. However, these models often face challenges in maintaining consist…
SimAvatar: Simulation-Ready Avatars with Layered Hair and Clothing
Xueting Li, Ye Yuan, Shalini De Mello +5
We introduce SimAvatar, a framework designed to generate simulation-ready clothed 3D human avatars from a text prompt. Current text-driven human avatar generation methods either mo…
Coherent3D: Coherent 3D Portrait Video Reconstruction via Triplane Fusion
Shengze Wang, Xueting Li, Chao Liu +5
Recent breakthroughs in single-image 3D portrait reconstruction have enabled telepresence systems to stream 3D portrait videos from a single camera in real-time, democratizing tele…
No Pose, No Problem: Surprisingly Simple 3D Gaussian Splats from Sparse Unposed Images
Botao Ye, Sifei Liu, Haofei Xu +4
We introduce NoPoSplat, a feed-forward model capable of reconstructing 3D scenes parameterized by 3D Gaussians from \textit{unposed} sparse multi-view images. Our model, trained ex…
Layout-your-3D: Controllable and Precise 3D Generation with 2D Blueprint
Junwei Zhou, Xueting Li, Lu Qi +1
We present Layout-Your-3D, a framework that allows controllable and compositional 3D generation from text prompts. Existing text-to-3D methods often struggle to generate assets wit…
Tex4D: Zero-shot 4D Scene Texturing with Video Diffusion Models
Jingzhi Bao, Xueting Li, Ming-Hsuan Yang
3D meshes are widely used in computer vision and graphics for their efficiency in animation and minimal memory use, playing a crucial role in movies, games, AR, and VR. However, cr…
Coherent 3D Portrait Video Reconstruction via Triplane Fusion
Shengze Wang, Xueting Li, Chao Liu +6
Recent breakthroughs in single-image 3D portrait reconstruction have enabled telepresence systems to stream 3D portrait videos from a single camera in real-time, potentially democr…
Gaga: Group Any Gaussians via 3D-aware Memory Bank
Weijie Lyu, Xueting Li, Abhijit Kundu +2
We introduce Gaga, a framework that reconstructs and segments open-world 3D scenes by leveraging inconsistent 2D masks predicted by zero-shot class-agnostic segmentation models. Co…
GAvatar: Animatable 3D Gaussian Avatars with Implicit Mesh Learning
Ye Yuan, Xueting Li, Yangyi Huang +4
Gaussian splatting has emerged as a powerful 3D representation that harnesses the advantages of both explicit (mesh) and implicit (NeRF) 3D representations. In this paper, we seek…
A Unified Approach for Text- and Image-guided 4D Scene Generation
Yufeng Zheng, Xueting Li, Koki Nagano +4
Large-scale diffusion generative models are greatly simplifying image, video and 3D asset creation from user-provided text prompts and images. However, the challenging problem of t…
Pyramid Diffusion for Fine 3D Large Scene Generation
Yuheng Liu, Xinke Li, Xueting Li +3
Diffusion models have shown remarkable results in generating 2D images and small-scale 3D objects. However, their application to the synthesis of large-scale 3D scenes has been rar…
3D Reconstruction with Generalizable Neural Fields using Scene Priors
Yang Fu, Shalini De Mello, Xueting Li +4
High-fidelity 3D scene reconstruction has been substantially advanced by recent progress in neural fields. However, most existing methods train a separate network from scratch for…
Generalizable One-shot Neural Head Avatar
Xueting Li, Shalini De Mello, Sifei Liu +3
We present a method that reconstructs and animates a 3D head avatar from a single-view portrait image. Existing methods either involve time-consuming optimization for a specific pe…
Zero-shot Pose Transfer for Unrigged Stylized 3D Characters
Jiashun Wang, Xueting Li, Sifei Liu +4
Transferring the pose of a reference avatar to stylized 3D characters of various shapes is a fundamental task in computer graphics. Existing methods either require the stylized cha…
TUVF: Learning Generalizable Texture UV Radiance Fields
An-Chieh Cheng, Xueting Li, Sifei Liu +1
Textures are a vital aspect of creating visually appealing and realistic 3D models. In this paper, we study the problem of generating high-fidelity texture given shapes of 3D asset…
Affordance Diffusion: Synthesizing Hand-Object Interactions
Yufei Ye, Xueting Li, Abhinav Gupta +5
Recent successes in image synthesis are powered by large-scale diffusion models. However, most methods are currently limited to either text- or image-conditioned generation for syn…
Physics-based Indirect Illumination for Inverse Rendering
Youming Deng, Xueting Li, Sifei Liu +1
We present a physics-based inverse rendering method that learns the illumination, geometry, and materials of a scene from posed multi-view RGB images. To model the illumination of…
Autoregressive 3D Shape Generation via Canonical Mapping
An-Chieh Cheng, Xueting Li, Sifei Liu +2
With the capacity of modeling long-range dependencies in sequential data, transformers have shown remarkable performances in a variety of generative tasks such as image, audio, and…