40 citations · 99 across the 28 of their papers we have counts for
6 papers · 2 filters
A Conditional Denoising Diffusion Probabilistic Model for Point Cloud Upsampling
Wentao Qu, Yuantian Shao, Lingwu Meng +2
Point cloud upsampling (PCU) enriches the representation of raw point clouds, significantly improving the performance in downstream tasks such as classification and reconstruction.…
UniDream: Unifying Diffusion Priors for Relightable Text-to-3D Generation
Zexiang Liu, Yangguang Li, Youtian Lin +7
Recent advancements in text-to-3D generation technology have significantly advanced the conversion of textual descriptions into imaginative well-geometrical and finely textured 3D…
Point Cloud Pre-training with Diffusion Models
Xiao Zheng, Xiaoshui Huang, Guofeng Mei +5
Pre-training a model and then fine-tuning it on downstream tasks has demonstrated significant success in the 2D image and NLP domains. However, due to the unordered and non-uniform…
Experts Weights Averaging: A New General Training Scheme for Vision Transformers
Yongqi Huang, Peng Ye, Xiaoshui Huang +4
Structural re-parameterization is a general training scheme for Convolutional Neural Networks (CNNs), which achieves performance improvement without increasing inference cost. As V…
UniG3D: A Unified 3D Object Generation Dataset
Qinghong Sun, Yangguang Li, ZeXiang Liu +5
The field of generative AI has a transformative impact on various areas, including virtual reality, autonomous driving, the metaverse, gaming, and robotics. Among these application…
LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark
Zhenfei Yin, Jiong Wang, Jianjian Cao +9
Large language models have emerged as a promising approach towards achieving general-purpose AI agents. The thriving open-source LLM community has greatly accelerated the developme…