activity
20242026
most citedVideoMV: Consistent Multi-View Generation Based on Large Video Generative Model

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Large Depth Completion Model from Sparse Observations

Zhu Yu, Zhengyi Zhao, Runmin Zhang +7

This work presents the Large Depth Completion Model (LDCM), a simple, effective, and robust framework for single-view metric depth estimation with sparse observations. Without rely…

cs.CV2026

Towards Consistent Video Geometry Estimation

Zhu Yu, Jingnan Gao, Runmin Zhang +9

This work presents ViGeo, a feed-forward foundation model for recovering spatially dense and temporally consistent geometry from video sequences. Built upon a plain transformer arc…

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.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★ 1 cited

VideoMV: Consistent Multi-View Generation Based on Large Video Generative Model

Qi Zuo, Xiaodong Gu, Lingteng Qiu +8

Generating multi-view images based on text or single-image prompts is a critical capability for the creation of 3D content. Two fundamental questions on this topic are what data we…

cs.CV2024

An Optimization Framework to Enforce Multi-View Consistency for Texturing 3D Meshes

Zhengyi Zhao, Chen Song, Xiaodong Gu +6

A fundamental problem in the texturing of 3D meshes using pre-trained text-to-image models is to ensure multi-view consistency. State-of-the-art approaches typically use diffusion…