1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CV2024
MoE Jetpack: From Dense Checkpoints to Adaptive Mixture of Experts for Vision Tasks
Xingkui Zhu, Yiran Guan, Dingkang Liang +3
The sparsely activated mixture of experts (MoE) model presents a promising alternative to traditional densely activated (dense) models, enhancing both quality and computational eff…
cs.CV2024★ 1 cited
Dynamic Adapter Meets Prompt Tuning: Parameter-Efficient Transfer Learning for Point Cloud Analysis
Xin Zhou, Dingkang Liang, Wei Xu +4
Point cloud analysis has achieved outstanding performance by transferring point cloud pre-trained models. However, existing methods for model adaptation usually update all model pa…
cs.CV2024
PointMamba: A Simple State Space Model for Point Cloud Analysis
Dingkang Liang, Xin Zhou, Wei Xu +5
Transformers have become one of the foundational architectures in point cloud analysis tasks due to their excellent global modeling ability. However, the attention mechanism has qu…