19 citations · 40 across the 15 of their papers we have counts for
16 papers
ReconPlusGen: Injecting Reconstruction Prior into Multi-view 3D Generation through Noise Inversion and Modulation
Jiarui Liu, Heng Li, Weiyu Li +7
Qualitative results and an illustration of our core idea. Top left: reconstruction results on benchmark images. Top right: reconstruction results on real-world images. Bottom: illu…
MeshFlow: Efficient Artistic Mesh Generation via MeshVAE and Flow-based Diffusion Transformer
Weiyu Li, Antoine Toisoul, Tom Monnier +4
We present MeshFlow, a new method for generating artist-like 3D meshes. Current mesh generators often adopt Auto-Regressive (AR) next-token prediction, a natural choice given the d…
SceneMaker: Open-set 3D Scene Generation with Decoupled De-occlusion and Pose Estimation Model
Yukai Shi, Weiyu Li, Zihao Wang +4
We propose a decoupled 3D scene generation framework called SceneMaker in this work. Due to the lack of sufficient open-set de-occlusion and pose estimation priors, existing method…
PoseMaster: A Unified 3D Native Framework for Stylized Pose Generation
Hongyu Yan, Kunming Luo, Weiyu Li +5
Pose stylization, which aims to synthesize stylized content aligning with target poses, serves as a fundamental task across 2D, 3D, and video domains. In the 3D realm, prevailing a…
UniTEX: Universal High Fidelity Generative Texturing for 3D Shapes
Yixun Liang, Kunming Luo, Xiao Chen +5
We present UniTEX, a novel two-stage 3D texture generation framework to create high-quality, consistent textures for 3D assets. Existing approaches predominantly rely on UV-based i…
Step1X-3D: Towards High-Fidelity and Controllable Generation of Textured 3D Assets
Weiyu Li, Xuanyang Zhang, Zheng Sun +15
While generative artificial intelligence has advanced significantly across text, image, audio, and video domains, 3D generation remains comparatively underdeveloped due to fundamen…
Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders
Rui Chen, Jianfeng Zhang, Yixun Liang +7
Recent 3D content generation pipelines commonly employ Variational Autoencoders (VAEs) to encode shapes into compact latent representations for diffusion-based generation. However,…
Multi-View Large Reconstruction Model via Geometry-Aware Positional Encoding and Attention
Mengfei Li, Xiaoxiao Long, Yixun Liang +6
Despite recent advancements in the Large Reconstruction Model (LRM) demonstrating impressive results, when extending its input from single image to multiple images, it exhibits ine…
CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refiner
Weiyu Li, Jiarui Liu, Hongyu Yan +5
We present a novel generative 3D modeling system, coined CraftsMan, which can generate high-fidelity 3D geometries with highly varied shapes, regular mesh topologies, and detailed…
BAGS: Building Animatable Gaussian Splatting from a Monocular Video with Diffusion Priors
Tingyang Zhang, Qingzhe Gao, Weiyu Li +2
Animatable 3D reconstruction has significant applications across various fields, primarily relying on artists' handcraft creation. Recently, some studies have successfully construc…
SweetDreamer: Aligning Geometric Priors in 2D Diffusion for Consistent Text-to-3D
Weiyu Li, Rui Chen, Xuelin Chen +1
It is inherently ambiguous to lift 2D results from pre-trained diffusion models to a 3D world for text-to-3D generation. 2D diffusion models solely learn view-agnostic priors and t…
Example-based Motion Synthesis via Generative Motion Matching
Weiyu Li, Xuelin Chen, Peizhuo Li +2
We present GenMM, a generative model that "mines" as many diverse motions as possible from a single or few example sequences. In stark contrast to existing data-driven methods, whi…
Patch-based 3D Natural Scene Generation from a Single Example
Weiyu Li, Xuelin Chen, Jue Wang +1
We target a 3D generative model for general natural scenes that are typically unique and intricate. Lacking the necessary volumes of training data, along with the difficulties of h…
MoCo-Flow: Neural Motion Consensus Flow for Dynamic Humans in Stationary Monocular Cameras
Xuelin Chen, Weiyu Li, Daniel Cohen-Or +2
Synthesizing novel views of dynamic humans from stationary monocular cameras is a specialized but desirable setup. This is particularly attractive as it does not require static sce…
DoveNet: Deep Image Harmonization via Domain Verification
Wenyan Cong, Jianfu Zhang, Li Niu +4
Image composition is an important operation in image processing, but the inconsistency between foreground and background significantly degrades the quality of composite image. Imag…
Image Harmonization Dataset iHarmony4: HCOCO, HAdobe5k, HFlickr, and Hday2night
Wenyan Cong, Jianfu Zhang, Li Niu +4
Image composition is an important operation in image processing, but the inconsistency between foreground and background significantly degrades the quality of composite image. Imag…