3 citations · 7 across the 4 of their papers we have counts for
4 papers
GET3D--: Learning GET3D from Unconstrained Image Collections
Fanghua Yu, Xintao Wang, Zheyuan Li +3
The demand for efficient 3D model generation techniques has grown exponentially, as manual creation of 3D models is time-consuming and requires specialized expertise. While generat…
InstructP2P: Learning to Edit 3D Point Clouds with Text Instructions
Jiale Xu, Xintao Wang, Yan-Pei Cao +3
Enhancing AI systems to perform tasks following human instructions can significantly boost productivity. In this paper, we present InstructP2P, an end-to-end framework for 3D shape…
RepSR: Training Efficient VGG-style Super-Resolution Networks with Structural Re-Parameterization and Batch Normalization
Xintao Wang, Chao Dong, Ying Shan
This paper explores training efficient VGG-style super-resolution (SR) networks with the structural re-parameterization technique. The general pipeline of re-parameterization is to…
Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution
Liangbin Xie, Xintao Wang, Chao Dong +2
Recent blind super-resolution (SR) methods typically consist of two branches, one for degradation prediction and the other for conditional restoration. However, our experiments sho…