SOTA2 Research · papers

Papers for “ade20k”

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

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Title	Authors	Year	Source
Token Cropr: Faster ViTs for Quite a Few Tasks	Benjamin Bergner, Christoph Lippert, Aravindh Mahendran	2024	arxiv 2412.00965
SPT: Sequence Prompt Transformer for Interactive Image Segmentation	Senlin Cheng, Haopeng Sun	2024	arxiv 2412.10224
Auto-Vocabulary Semantic Segmentation	Osman Ülger, Maksymilian Kulicki, Yuki Asano	2023	arxiv 2312.04539
RTFormer: Efficient Design for Real-Time Semantic Segmentation with Transformer	Jian Wang, Chenhui Gou, Qiman Wu	2022	arxiv 2210.07124
Delving into Transformer for Incremental Semantic Segmentation	Zekai Xu, Mingyi Zhang, Jiayue Hou	2022	arxiv 2211.10253
SegViT: Semantic Segmentation with Plain Vision Transformers	Bowen Zhang, Zhi Tian, Quan Tang	2022	arxiv 2210.05844
Rethinking Mobile Block for Efficient Attention-based Models	Jiangning Zhang, Xiangtai Li, Jian Li	2023	arxiv 2301.01146
Gramian Attention Heads are Strong yet Efficient Vision Learners	Jongbin Ryu, Dongyoon Han, Jongwoo Lim	2023	arxiv 2310.16483
Relating Input Concepts to Convolutional Neural Network Decisions	Ning Xie, Md Kamruzzaman Sarker, Derek Doran	2017	arxiv 1711.08006
LangHOPS: Language Grounded Hierarchical Open-Vocabulary Part Segmentation	Yang Miao, Jan-Nico Zaech, Xi Wang	2025	arxiv 2510.25263
Mamba2D: A Natively Multi-Dimensional State-Space Model for Vision Tasks