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Found 4 papers, 1 papers with code
CARE Transformer: Mobile-Friendly Linear Visual Transformer via Decoupled Dual Interaction
In this paper, we propose a new de\textbf{C}oupled du\textbf{A}l-interactive linea\textbf{R} att\textbf{E}ntion (CARE) mechanism, revealing that features' decoupling and interaction can fully unleash the power of linear attention.
TeFF: Tracking-enhanced Forgetting-free Few-shot 3D LiDAR Semantic Segmentation
However, this approach introduces a data imbalance biased to novel data that presents a new challenge of catastrophic forgetting.
RMem: Restricted Memory Banks Improve Video Object Segmentation
With recent video object segmentation (VOS) benchmarks evolving to challenging scenarios, we revisit a simple but overlooked strategy: restricting the size of memory banks.
Few-shot 3D LiDAR Semantic Segmentation for Autonomous Driving
Thus, we propose a few-shot 3D LiDAR semantic segmentation method that predicts both novel classes and base classes simultaneously.
Autonomous Driving
Generalized Few-Shot Semantic Segmentation
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