no code implementations • 28 Apr 2024 • Guanchun Wang, Xiangrong Zhang, Zelin Peng, Tianyang Zhang, Xiuping Jia, Licheng Jiao
In S$^2$Mamba, two selective structured state space models through different dimensions are designed for feature extraction, one for spatial, and the other for spectral, along with a spatial-spectral mixture gate for optimal fusion.
no code implementations • 28 Nov 2023 • Zelin Peng, Zhengqin Xu, Zhilin Zeng, Lingxi Xie, Qi Tian, Wei Shen
Parameter-efficient fine-tuning (PEFT) is an effective methodology to unleash the potential of large foundation models in novel scenarios with limited training data.
no code implementations • 28 Aug 2023 • Zelin Peng, Zhengqin Xu, Zhilin Zeng, Xiaokang Yang, Wei Shen
Most existing fine-tuning methods attempt to bridge the gaps among different scenarios by introducing a set of new parameters to modify SAM's original parameter space.
no code implementations • ICCV 2023 • Zelin Peng, Guanchun Wang, Lingxi Xie, Dongsheng Jiang, Wei Shen, Qi Tian
Seed area generation is usually the starting point of weakly supervised semantic segmentation (WSSS).
Multi-Label Classification Weakly supervised Semantic Segmentation +1
no code implementations • 4 Jul 2022 • Wei Shen, Zelin Peng, Xuehui Wang, Huayu Wang, Jiazhong Cen, Dongsheng Jiang, Lingxi Xie, Xiaokang Yang, Qi Tian
Next, we summarize the existing label-efficient image segmentation methods from a unified perspective that discusses an important question: how to bridge the gap between weak supervision and dense prediction -- the current methods are mostly based on heuristic priors, such as cross-pixel similarity, cross-label constraint, cross-view consistency, and cross-image relation.
no code implementations • 21 Apr 2022 • Guanchun Wang, Xiangrong Zhang, Zelin Peng, Xu Tang, Huiyu Zhou, Licheng Jiao
In the exploiting stage, we utilize the extracted NDI to construct a novel negative contrastive learning mechanism and a negative guided instance selection strategy for dealing with the issues of part domination and missing instances, respectively.
no code implementations • 3 Aug 2021 • Xiangrong Zhang, Zelin Peng, Peng Zhu, Tianyang Zhang, Chen Li, Huiyu Zhou, Licheng Jiao
Semantic segmentation has been continuously investigated in the last ten years, and majority of the established technologies are based on supervised models.