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Papers for “ade20k”

Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.

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TitleAuthorsYearSource
Semantic Understanding of Scenes through the ADE20K DatasetBolei Zhou, Hang Zhao, Xavier Puig2016arxiv 1608.05442
Dilated Neighborhood Attention TransformerAli Hassani, Humphrey Shi2022arxiv 2209.15001
MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input FeaturesShakti N. Wadekar, Abhishek Chaurasia2022arxiv 2209.15159
The Missing Point in Vision Transformers for Universal Image SegmentationSajjad Shahabodini, Mobina Mansoori, Farnoush Bayatmakou2025arxiv 2505.19795
Cross-Stage Attention Propagation for Efficient Semantic SegmentationBeoungwoo Kang2026arxiv 2604.05431
Region Rebalance for Long-Tailed Semantic SegmentationJiequan Cui, Yuhui Yuan, Zhisheng Zhong2022arxiv 2204.01969
PaCa-ViT: Learning Patch-to-Cluster Attention in Vision TransformersRyan Grainger, Thomas Paniagua, Xi Song2022arxiv 2203.11987
Class-level Multiple Distributions Representation are Necessary for Semantic SegmentationJianjian Yin, Zhichao Zheng, Yanhui Gu2023arxiv 2303.08029
1st Place Solution of The Robust Vision Challenge 2022 Semantic Segmentation TrackJunfei Xiao, Zhichao Xu, Shiyi Lan2022arxiv 2210.12852
The Surprising Effectiveness of Canonical Knowledge Distillation for Semantic SegmentationMuhammad Ali, Kevin Alexander Laube, Madan Ravi Ganesh2026arxiv 2604.25530
DSNet: A Novel Way to Use Atrous Convolutions in Semantic SegmentationZilu Guo, Liuyang Bian, Xuan Huang2024arxiv 2406.03702
Context-Guided Spatial Feature Reconstruction for Efficient Semantic SegmentationZhenliang Ni, Xinghao Chen, Yingjie Zhai2024arxiv 2405.06228
Semantic Segmentation via Highly Fused Convolutional Network with Multiple Soft Cost FunctionsTao Yang, Yan Wu, Junqiao Zhao2018arxiv 1801.01317
ARTA: Adaptive Mixed-Resolution Token Allocation for Efficient Dense Feature ExtractionDavid Hagerman, Roman Naeem, Erik Brorsson2026arxiv 2603.26258
BiCANet: Bi-directional Contextual Aggregating Network for Image Semantic SegmentationQuan Zhou, Dechun Cong, Bin Kang2020arxiv 2003.09669
Switchable Whitening for Deep Representation LearningXingang Pan, Xiaohang Zhan, Jianping Shi2019arxiv 1904.09739
Revisiting Efficient Semantic Segmentation: Learning Offsets for Better Spatial and Class Feature AlignmentShi-Chen Zhang, Yunheng Li, Yu-Huan Wu2025arxiv 2508.08811
Multi-Scale High-Resolution Vision Transformer for Semantic SegmentationJiaqi Gu, Hyoukjun Kwon, Dilin Wang2021arxiv 2111.01236
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with TransformersSixiao Zheng, Jiachen Lu, Hengshuang Zhao2020arxiv 2012.15840
SegGen: Supercharging Segmentation Models with Text2Mask and Mask2Img SynthesisHanrong Ye, Jason Kuen, Qing Liu2023arxiv 2311.03355