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20142023
most citedSTC: A Simple to Complex Framework for Weakly-supervised Semantic Segmentation

619 citations · 3.7k across the 114 of their papers we have counts for

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Showing 2020 · cs.CVShow all

8 papers · 2 filters

cs.CV2020

Ada-Segment: Automated Multi-loss Adaptation for Panoptic Segmentation

Gengwei Zhang, Yiming Gao, Hang Xu +3

Panoptic segmentation that unifies instance segmentation and semantic segmentation has recently attracted increasing attention. While most existing methods focus on designing novel…

cs.CV2020

Towards Robust Partially Supervised Multi-Structure Medical Image Segmentation on Small-Scale Data

Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang +3

The data-driven nature of deep learning (DL) models for semantic segmentation requires a large number of pixel-level annotations. However, large-scale and fully labeled medical dat…

cs.CV2020★ 17 cited

Auto-Panoptic: Cooperative Multi-Component Architecture Search for Panoptic Segmentation

Yangxin Wu, Gengwei Zhang, Hang Xu +2

Panoptic segmentation is posed as a new popular test-bed for the state-of-the-art holistic scene understanding methods with the requirement of simultaneously segmenting both foregr…

cs.CV2020★ 21 cited

CurveLane-NAS: Unifying Lane-Sensitive Architecture Search and Adaptive Point Blending

Hang Xu, Shaoju Wang, Xinyue Cai +3

We address the curve lane detection problem which poses more realistic challenges than conventional lane detection for better facilitating modern assisted/autonomous driving system…

cs.CV2020★ 8 cited

Bidirectional Graph Reasoning Network for Panoptic Segmentation

Yangxin Wu, Gengwei Zhang, Yiming Gao +4

Recent researches on panoptic segmentation resort to a single end-to-end network to combine the tasks of instance segmentation and semantic segmentation. However, prior models only…

cs.CV2020★ 2 cited

Linguistically Driven Graph Capsule Network for Visual Question Reasoning

Qingxing Cao, Xiaodan Liang, Keze Wang +1

Recently, studies of visual question answering have explored various architectures of end-to-end networks and achieved promising results on both natural and synthetic datasets, whi…