1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2023
OmniSeg3D: Omniversal 3D Segmentation via Hierarchical Contrastive Learning
Haiyang Ying, Yixuan Yin, Jinzhi Zhang +4
Towards holistic understanding of 3D scenes, a general 3D segmentation method is needed that can segment diverse objects without restrictions on object quantity or categories, whil…
cs.CV2023★ 1 cited
Dual Meta-Learning with Longitudinally Generalized Regularization for One-Shot Brain Tissue Segmentation Across the Human Lifespan
Yongheng Sun, Fan Wang, Jun Shu +3
Brain tissue segmentation is essential for neuroscience and clinical studies. However, segmentation on longitudinal data is challenging due to dynamic brain changes across the life…
cs.CV2023★ 1 cited
Points-to-3D: Bridging the Gap between Sparse Points and Shape-Controllable Text-to-3D Generation
Chaohui Yu, Qiang Zhou, Jingliang Li +3
Text-to-3D generation has recently garnered significant attention, fueled by 2D diffusion models trained on billions of image-text pairs. Existing methods primarily rely on score d…