1 citations · 1 across the 2 of their papers we have counts for
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Non-confusing Generation of Customized Concepts in Diffusion Models
Wang Lin, Jingyuan Chen, Jiaxin Shi +8
We tackle the common challenge of inter-concept visual confusion in compositional concept generation using text-guided diffusion models (TGDMs). It becomes even more pronounced in…
Unsupervised Discovery of Interpretable Directions in h-space of Pre-trained Diffusion Models
Zijian Zhang, Luping Liu, Zhijie Lin +2
We propose the first unsupervised and learning-based method to identify interpretable directions in h-space of pre-trained diffusion models. Our method is derived from an existing…
3DRP-Net: 3D Relative Position-aware Network for 3D Visual Grounding
Zehan Wang, Haifeng Huang, Yang Zhao +5
3D visual grounding aims to localize the target object in a 3D point cloud by a free-form language description. Typically, the sentences describing the target object tend to provid…
Distilling Coarse-to-Fine Semantic Matching Knowledge for Weakly Supervised 3D Visual Grounding
Zehan Wang, Haifeng Huang, Yang Zhao +5
3D visual grounding involves finding a target object in a 3D scene that corresponds to a given sentence query. Although many approaches have been proposed and achieved impressive p…