42 citations · 110 across the 21 of their papers we have counts for
9 papers · 1 filter
Towards Multimodal Open-Set Domain Generalization and Adaptation through Self-supervision
Hao Dong, Eleni Chatzi, Olga Fink
The task of open-set domain generalization (OSDG) involves recognizing novel classes within unseen domains, which becomes more challenging with multiple modalities as input. Existi…
No Time to Train: Empowering Non-Parametric Networks for Few-shot 3D Scene Segmentation
Xiangyang Zhu, Renrui Zhang, Bowei He +6
To reduce the reliance on large-scale datasets, recent works in 3D segmentation resort to few-shot learning. Current 3D few-shot segmentation methods first pre-train models on 'see…
Scalable Geometric Fracture Assembly via Co-creation Space among Assemblers
Ruiyuan Zhang, Jiaxiang Liu, Zexi Li +3
Geometric fracture assembly presents a challenging practical task in archaeology and 3D computer vision. Previous methods have focused solely on assembling fragments based on seman…
SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization
Hao Dong, Ismail Nejjar, Han Sun +2
In real-world scenarios, achieving domain generalization (DG) presents significant challenges as models are required to generalize to unknown target distributions. Generalizing to…
Improving Compositional Text-to-image Generation with Large Vision-Language Models
Song Wen, Guian Fang, Renrui Zhang +3
Recent advancements in text-to-image models, particularly diffusion models, have shown significant promise. However, compositional text-to-image models frequently encounter difficu…
Less is More: Towards Efficient Few-shot 3D Semantic Segmentation via Training-free Networks
Xiangyang Zhu, Renrui Zhang, Bowei He +4
To reduce the reliance on large-scale datasets, recent works in 3D segmentation resort to few-shot learning. Current 3D few-shot semantic segmentation methods first pre-train the m…