18 citations · 23 across the 4 of their papers we have counts for
4 papers
GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation
Yinghao Xu, Zifan Shi, Wang Yifan +5
We introduce GRM, a large-scale reconstructor capable of recovering a 3D asset from sparse-view images in around 0.1s. GRM is a feed-forward transformer-based model that efficientl…
DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Model
Yinghao Xu, Hao Tan, Fujun Luan +8
We propose \textbf{DMV3D}, a novel 3D generation approach that uses a transformer-based 3D large reconstruction model to denoise multi-view diffusion. Our reconstruction model inco…
Exploring Sparse MoE in GANs for Text-conditioned Image Synthesis
Jiapeng Zhu, Ceyuan Yang, Kecheng Zheng +3
Due to the difficulty in scaling up, generative adversarial networks (GANs) seem to be falling from grace on the task of text-conditioned image synthesis. Sparsely-activated mixtur…
Design of Coded Caching Schemes with Linear Subpacketizations Based on Injective Arc Coloring of Regular Digraphs
Xianzhang Wu, Minquan Cheng, Li Chen +2
Coded caching is an effective technique to decongest the amount of traffic in the backhaul link. In such a scheme, each file hosted in the server is divided into a number of packet…