most citedParaFormer: Parallel Attention Transformer for Efficient Feature Matching

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cs.CV2025

DeCLIP: Decoupled Learning for Open-Vocabulary Dense Perception

Junjie Wang, Bin Chen, Yulin Li +3

Dense visual prediction tasks have been constrained by their reliance on predefined categories, limiting their applicability in real-world scenarios where visual concepts are unbou…

cs.CV2023★ 2 cited

ParaFormer: Parallel Attention Transformer for Efficient Feature Matching

Xiaoyong Lu, Yaping Yan, Bin Kang +1

Heavy computation is a bottleneck limiting deep-learningbased feature matching algorithms to be applied in many realtime applications. However, existing lightweight networks optimi…