39 citations · 92 across the 18 of their papers we have counts for
18 papers
OmniControlNet: Dual-stage Integration for Conditional Image Generation
Yilin Wang, Haiyang Xu, Xiang Zhang +4
We provide a two-way integration for the widely adopted ControlNet by integrating external condition generation algorithms into a single dense prediction method and incorporating i…
Grounded Compositional and Diverse Text-to-3D with Pretrained Multi-View Diffusion Model
Xiaolong Li, Jiawei Mo, Ying Wang +7
In this paper, we propose an effective two-stage approach named Grounded-Dreamer to generate 3D assets that can accurately follow complex, compositional text prompts while achievin…
Bayesian Diffusion Models for 3D Shape Reconstruction
Haiyang Xu, Yu Lei, Zeyuan Chen +4
We present Bayesian Diffusion Models (BDM), a prediction algorithm that performs effective Bayesian inference by tightly coupling the top-down (prior) information with the bottom-u…
On the Scalability of Diffusion-based Text-to-Image Generation
Hao Li, Yang Zou, Ying Wang +7
Scaling up model and data size has been quite successful for the evolution of LLMs. However, the scaling law for the diffusion based text-to-image (T2I) models is not fully explore…
HOIDiffusion: Generating Realistic 3D Hand-Object Interaction Data
Mengqi Zhang, Yang Fu, Zheng Ding +3
3D hand-object interaction data is scarce due to the hardware constraints in scaling up the data collection process. In this paper, we propose HOIDiffusion for generating realistic…
AffordanceLLM: Grounding Affordance from Vision Language Models
Shengyi Qian, Weifeng Chen, Min Bai +3
Affordance grounding refers to the task of finding the area of an object with which one can interact. It is a fundamental but challenging task, as a successful solution requires th…