no code implementations • 6 Mar 2024 • Weihao Jiang, Guodong Liu, Di He, Kun He
However, as a non-end-to-end training method, indicating the meta-training stage can only begin after the completion of pre-training, Meta-Baseline suffers from higher training cost and suboptimal performance due to the inherent conflicts of the two training stages.
1 code implementation • 23 Jan 2024 • Zhaozhi Xie, Bochen Guan, Weihao Jiang, Muyang Yi, Yue Ding, Hongtao Lu, Lei Zhang
In this paper, we introduce a novel prompt-driven adapter into SAM, namely Prompt Adapter Segment Anything Model (PA-SAM), aiming to enhance the segmentation mask quality of the original SAM.
1 code implementation • 15 Jun 2023 • Haoran Deng, Yang Yang, Jiahe Li, Haoyang Cai, ShiLiang Pu, Weihao Jiang
Network embedding, a graph representation learning method illustrating network topology by mapping nodes into lower-dimension vectors, is challenging to accommodate the ever-changing dynamic graphs in practice.
1 code implementation • 1 Dec 2021 • Weihao Jiang, Dongdong Yu, Zhaozhi Xie, Yaoyi Li, Zehuan Yuan, Hongtao Lu
For emerging content-based feature fusion, most existing matting methods only focus on local features which lack the guidance of a global feature with strong semantic information related to the interesting object.
Ranked #4 on Image Matting on Composition-1K
no code implementations • 4 Jun 2020 • Weihao Jiang, Zhaozhi Xie, Yaoyi Li, Chang Liu, Hongtao Lu
Many of these applications need to perform a real-time and efficient prediction for semantic segmentation with a light-weighted network.