10 citations · 17 across the 7 of their papers we have counts for
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cs.CV2023
MaskConver: Revisiting Pure Convolution Model for Panoptic Segmentation
Abdullah Rashwan, Jiageng Zhang, Ali Taalimi +5
In recent years, transformer-based models have dominated panoptic segmentation, thanks to their strong modeling capabilities and their unified representation for both semantic and…
cs.CV2023★ 1 cited
Two-Step Active Learning for Instance Segmentation with Uncertainty and Diversity Sampling
Ke Yu, Stephen Albro, Giulia DeSalvo +5
Training high-quality instance segmentation models requires an abundance of labeled images with instance masks and classifications, which is often expensive to procure. Active lear…
cs.CV2023★ 10 cited
DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model
Xiuye Gu, Yin Cui, Jonathan Huang +8
Observing the close relationship among panoptic, semantic and instance segmentation tasks, we propose to train a universal multi-dataset multi-task segmentation model: DaTaSeg.We u…