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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
Learning Implicit Feature Alignment Function for Semantic SegmentationHanzhe Hu, Yinbo Chen, Jiarui Xu2022arxiv 2206.08655
Graph Reasoning Transformer for Image ParsingDong Zhang, Jinhui Tang, Kwang-Ting Cheng2022arxiv 2209.09545
CoCAViT: Compact Vision Transformer with Robust Global CoordinationXuyang Wang, Lingjuan Miao, Zhiqiang Zhou2025arxiv 2508.05307
Learning Yourself: Class-Incremental Semantic Segmentation with Language-Inspired Bootstrapped DisentanglementRuitao Wu, Yifan Zhao, Jia Li2025arxiv 2509.00527
Open-world Instance Segmentation: Top-down Learning with Bottom-up SupervisionTarun Kalluri, Weiyao Wang, Heng Wang2023arxiv 2303.05503
Make a Strong Teacher with Label Assistance: A Novel Knowledge Distillation Approach for Semantic SegmentationShoumeng Qiu, Jie Chen, Xinrun Li2024arxiv 2407.13254
Dynamic Neural Representational Decoders for High-Resolution Semantic SegmentationBowen Zhang, Yifan Liu, Zhi Tian2021arxiv 2107.14428
Mining Contextual Information Beyond Image for Semantic SegmentationZhenchao Jin, Tao Gong, Dongdong Yu2021arxiv 2108.11819
ISNet: Integrate Image-Level and Semantic-Level Context for Semantic SegmentationZhenchao Jin, Bin Liu, Qi Chu2021arxiv 2108.12382
DAT++: Spatially Dynamic Vision Transformer with Deformable AttentionZhuofan Xia, Xuran Pan, Shiji Song2023arxiv 2309.01430
Denoised Non-Local Neural Network for Semantic SegmentationQi Song, Jie Li, Hao Guo2021arxiv 2110.14200
Pale Transformer: A General Vision Transformer Backbone with Pale-Shaped AttentionSitong Wu, Tianyi Wu, Haoru Tan2021arxiv 2112.14000
Panoptic, Instance and Semantic Relations: A Relational Context Encoder to Enhance Panoptic SegmentationShubhankar Borse, Hyojin Park, Hong Cai2022arxiv 2204.05370
Panoptic Edge DetectionYuan Hu, Yingtian Zou, Jiashi Feng2019arxiv 1906.00590
An Empirical Study of Multimodal Model MergingYi-Lin Sung, Linjie Li, Kevin Lin2023arxiv 2304.14933
Mixed Autoencoder for Self-supervised Visual Representation LearningKai Chen, Zhili Liu, Lanqing Hong2023arxiv 2303.17152
MixReorg: Cross-Modal Mixed Patch Reorganization is a Good Mask Learner for Open-World Semantic SegmentationKaixin Cai, Pengzhen Ren, Yi Zhu2023arxiv 2308.04829
PeLK: Parameter-efficient Large Kernel ConvNets with Peripheral ConvolutionHonghao Chen, Xiangxiang Chu, Yongjian Ren2024arxiv 2403.07589
HIRI-ViT: Scaling Vision Transformer with High Resolution InputsTing Yao, Yehao Li, Yingwei Pan2024arxiv 2403.11999
CLIP-DINOiser: Teaching CLIP a few DINO tricks for open-vocabulary semantic segmentationMonika Wysoczańska, Oriane Siméoni, Michaël Ramamonjisoa2023arxiv 2312.12359