Jul 3, 2024 · In this paper, we introduce an Efficient Vision Transformer with Token-selective and Merging Strategies (TSMVT), which significantly improves underwater fine- ...
In this paper, we introduce an Efficient. Vision Transformer with Token-selective and Merging Strategies ... In recent years, Autonomous Underwater Vehicles (AUVs).
Efficient Vision Transformer With Token-Selective and Merging Strategies for Autonomous Underwater Vehicles. IEEE Internet Things J. 11(19): 32129-32142 ...
Efficient Vision Transformer With Token-Selective and Merging Strategies for Autonomous Underwater Vehicles · Article. January 2024. ·. 1 Read. ·. 1 Citation.
Efficient Vision Transformer With Token-Selective and Merging Strategies for Autonomous Underwater Vehicles. Y Jiang, Y Zhang, Y Wang, Q Guo, M Zhao, H Qin.
In this paper, we introduce an Efficient Vision Transformer with Token-selective and Merging Strategies (TSMVT), which significantly improves underwater fine- ...
Jun 13, 2024 · In this paper, we propose a novel token selective attention approach, \ours, which can make any vision transformer more efficient by selecting ...
Missing: Underwater Vehicles.
Mar 23, 2024 · (arXiv 2023.09) A survey on efficient vision transformers: algorithms, techniques, and performance benchmarking. [Paper]. (arXiv 2023.07) A ...
Compared with token pruning methods, Token Merger is more effective in preserving meaning contextual cues, thus performs and generalizes substantially better in ...
Missing: Selective Autonomous Underwater Vehicles.
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Apr 24, 2023 · In the TS Transformer Layer, TSSA is a sparse selective attention mechanism that generates a mask based on the similarity between tokens so as ...
Missing: Merging Strategies