most citedMVImgNet2.0: A Larger-scale Dataset of Multi-view Images

1 citations · 1 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2025

LAM: Large Avatar Model for One-shot Animatable Gaussian Head

Yisheng He, Xiaodong Gu, Xiaodan Ye +6

We present LAM, an innovative Large Avatar Model for animatable Gaussian head reconstruction from a single image. Unlike previous methods that require extensive training on capture…

cs.CV2025

LHM: Large Animatable Human Reconstruction Model from a Single Image in Seconds

Lingteng Qiu, Xiaodong Gu, Peihao Li +8

Animatable 3D human reconstruction from a single image is a challenging problem due to the ambiguity in decoupling geometry, appearance, and deformation. Recent advances in 3D huma…

cs.CV2024

MCMat: Multiview-Consistent and Physically Accurate PBR Material Generation

Shenhao Zhu, Lingteng Qiu, Xiaodong Gu +11

Existing 2D methods utilize UNet-based diffusion models to generate multi-view physically-based rendering (PBR) maps but struggle with multi-view inconsistency, while some 3D metho…

cs.CV2024

AniGS: Animatable Gaussian Avatar from a Single Image with Inconsistent Gaussian Reconstruction

Lingteng Qiu, Shenhao Zhu, Qi Zuo +9

Generating animatable human avatars from a single image is essential for various digital human modeling applications. Existing 3D reconstruction methods often struggle to capture f…

cs.CV20241 cited

MVImgNet2.0: A Larger-scale Dataset of Multi-view Images

Xiaoguang Han, Yushuang Wu, Luyue Shi +7

MVImgNet is a large-scale dataset that contains multi-view images of ~220k real-world objects in 238 classes. As a counterpart of ImageNet, it introduces 3D visual signals via mult…

cs.CV2024

Surface-Centric Modeling for High-Fidelity Generalizable Neural Surface Reconstruction

Rui Peng, Shihe Shen, Kaiqiang Xiong +4

Reconstructing the high-fidelity surface from multi-view images, especially sparse images, is a critical and practical task that has attracted widespread attention in recent years.…