activity
20192025
most citedTDAPNet: Prototype Network with Recurrent Top-Down Attention for Robust Object Classification under Partial Occlusion

17 citations · 21 across the 10 of their papers we have counts for

collaborators
Showing 2023Show all

2 papers · 1 filter

cs.CV2023★ 3 cited

Segment Any 3D Gaussians

Jiazhong Cen, Jiemin Fang, Chen Yang +4

This paper presents SAGA (Segment Any 3D GAussians), a highly efficient 3D promptable segmentation method based on 3D Gaussian Splatting (3D-GS). Given 2D visual prompts as input,…

cs.CV2023★ 1 cited

Parameter Efficient Fine-tuning via Cross Block Orchestration for Segment Anything Model

Zelin Peng, Zhengqin Xu, Zhilin Zeng +3

Parameter-efficient fine-tuning (PEFT) is an effective methodology to unleash the potential of large foundation models in novel scenarios with limited training data. In the compute…