most citedWonder3D++: Cross-domain Diffusion for High-fidelity 3D Generation from a Single Image

2 citations · 2 across the 12 of their papers we have counts for

collaborators

16 papers

hep-th2026

Holographic theory of non-invertible gravitational anomalies

Xiao-Gang Wen

We review a many-body formulation of gravitational anomalies as obstructions to realizing the complete low-energy data by a local {\it bosonic} lattice quantum system of the same d…

cs.CV2026

PURE: Refining Feed-forward 3D Reconstruction with Unlabeled Post-training

Yaolong Zhu, Peng Li, Jiahao Lu +8

Feed-forward 3D reconstruction models have achieved remarkable progress through large-scale training and strong learned priors. However, they remain fragile when applied to dynamic…

cs.CV2026

ForcingBooster: Adaptive Patch-wise Denoising for Fast Autoregressive Video Diffusion

Zekai Gu, Peng Wang, Jiahao Lu +3

Autoregressive video diffusion models have become a leading approach to real-time interactive video generation and video world modeling. However, existing methods typically allocat…

cs.CV2026

WAT3R: Feedforward Underwater 3D Reconstruction

Jiayi Xu, Jiahao Lu, Ziqiang Zheng +4

Reliable feedforward underwater 3D reconstruction remains challenging due to severe light attenuation and backscattering, which degrade visual quality and disrupt feature consisten…

cs.GR2026

QuadLink: Autoregressive Quad-Dominant Mesh Generation via Point-Relation Learning

Yiheng Zhang, Zhe Zhu, Tingrui Shen +11

The generation of production-ready quad-dominant meshes is a cornerstone of modern 3D content creation. Generating anisotropic quad-dominant meshes from point clouds is challenging…

cs.CV2026

RecGen3D: Reconstruction-Guided 3D Generation in a Shared Canonical Space

Zhisheng Huang, Jiahao Chen, Cheng Lin +10

Sparse-view 3D modeling represents a fundamental tension between reconstruction fidelity and generative plausibility. While feed-forward reconstruction excels in efficiency and inp…

cs.CV2026

GO-Renderer: Generative Object Rendering with 3D-aware Controllable Video Diffusion Models

Zekai Gu, Shuoxuan Feng, Yansong Wang +6

Reconstructing a renderable 3D model from images is a useful but challenging task. Recent feedforward 3D reconstruction methods have demonstrated remarkable success in efficiently…

cs.CV2026

HGGT: Robust and Flexible 3D Hand Mesh Reconstruction from Uncalibrated Images

Yumeng Liu, Xiao-Xiao Long, Marc Habermann +5

Recovering high-fidelity 3D hand geometry from images is a critical task in computer vision, holding significant value for domains such as robotics, animation and VR/AR. Crucially,…

cs.CV2026

Know3D: Prompting 3D Generation with Knowledge from Vision-Language Models

Wenyue Chen, Wenjue Chen, Peng Li +6

Recent advances in 3D generation have improved the fidelity and geometric details of synthesized 3D assets. However, due to the inherent ambiguity of single-view observations and t…

cs.CV2026

FlexAM: Flexible Appearance-Motion Decomposition for Versatile Video Generation Control

Mingzhi Sheng, Zekai Gu, Peng Li +4

Effective and generalizable control in video generation remains a significant challenge. While many methods rely on ambiguous or task-specific signals, we argue that a fundamental…

cs.CV2026

RefAny3D: 3D Asset-Referenced Diffusion Models for Image Generation

Hanzhuo Huang, Qingyang Bao, Zekai Gu +4

In this paper, we propose a 3D asset-referenced diffusion model for image generation, exploring how to integrate 3D assets into image diffusion models. Existing reference-based ima…

cs.CV2026

CoMoVi: Co-Generation of 3D Human Motions and Realistic Videos

Chengfeng Zhao, Jiazhi Shu, Yubo Zhao +7

In this paper, we find that the generation of 3D human motions and 2D human videos is intrinsically coupled. 3D motions provide the structural prior for plausibility and consistenc…

cs.CV2025

TrackingWorld: World-centric Monocular 3D Tracking of Almost All Pixels

Jiahao Lu, Weitao Xiong, Jiacheng Deng +6

Monocular 3D tracking aims to capture the long-term motion of pixels in 3D space from a single monocular video and has witnessed rapid progress in recent years. However, we argue t…

cs.CV2025★ 2 cited

Wonder3D++: Cross-domain Diffusion for High-fidelity 3D Generation from a Single Image

Yuxiao Yang, Xiao-Xiao Long, Zhiyang Dou +7

In this work, we introduce \textbf{Wonder3D++}, a novel method for efficiently generating high-fidelity textured meshes from single-view images. Recent methods based on Score Disti…

cs.CV2025

SyncHuman: Synchronizing 2D and 3D Generative Models for Single-view Human Reconstruction

Wenyue Chen, Peng Li, Wangguandong Zheng +6

Photorealistic 3D full-body human reconstruction from a single image is a critical yet challenging task for applications in films and video games due to inherent ambiguities and se…

cs.CV2025

PartSAM: A Scalable Promptable Part Segmentation Model Trained on Native 3D Data

Zhe Zhu, Le Wan, Rui Xu +6

Segmenting 3D objects into parts is a long-standing challenge in computer vision. To overcome taxonomy constraints and generalize to unseen 3D objects, recent works turn to open-wo…