1 code implementation • 11 Mar 2024 • Guobao Xiao, Jun Yu, Jiayi Ma, Deng-Ping Fan, Ling Shao
The principle of LSC is to preserve the latent semantic consensus in both data points and model hypotheses.
1 code implementation • 7 Jan 2024 • Xiangyang Miao, Guobao Xiao, Shiping Wang, Jun Yu
In our approach, we design a distinctive self-attention block to capture global context and parallel process it with the established local context learning module, which enables us to simultaneously capture both local and global consensuses.
no code implementations • 26 Dec 2023 • Junwen Guo, Guobao Xiao, Shiping Wang, Jun Yu
To further apply the recalibrated graph contexts to the global domain, we propose the Graph Context Guidance Transformer.
1 code implementation • 14 Dec 2023 • Tangfei Liao, Xiaoqin Zhang, Li Zhao, Tao Wang, Guobao Xiao
Then, we model these visual cues and correspondences by a joint visual-spatial fusion module, simultaneously embedding visual cues into correspondences for pruning.
4 code implementations • 27 Mar 2022 • Ge-Peng Ji, Guobao Xiao, Yu-Cheng Chou, Deng-Ping Fan, Kai Zhao, Geng Chen, Luc van Gool
We present the first comprehensive video polyp segmentation (VPS) study in the deep learning era.
Ranked #2 on Video Polyp Segmentation on SUN-SEG-Easy (Unseen)
1 code implementation • ICCV 2021 • Zhen Zhong, Guobao Xiao, Linxin Zheng, Yan Lu, Jiayi Ma
We develop a conceptually simple, flexible, and effective framework (named T-Net) for two-view correspondence learning.
no code implementations • 29 Dec 2020 • Shuyuan Lin, Xing Wang, Guobao Xiao, Yan Yan, Hanzi Wang
In this paper, we propose a novel hierarchical representation via message propagation (HRMP) method for robust model fitting, which simultaneously takes advantages of both the consensus analysis and the preference analysis to estimate the parameters of multiple model instances from data corrupted by outliers, for robust model fitting.
no code implementations • 13 Feb 2020 • Shuyuan Lin, Guobao Xiao, Yan Yan, David Suter, Hanzi Wang
Recently, some hypergraph-based methods have been proposed to deal with the problem of model fitting in computer vision, mainly due to the superior capability of hypergraph to represent the complex relationship between data points.
no code implementations • 9 Dec 2019 • Tao Wang, Xuming He, Yuanzheng Cai, Guobao Xiao
We present a context aware object detection method based on a retrieve-and-transform scene layout model.
no code implementations • 3 May 2018 • Guobao Xiao, Hanzi Wang, Yan Yan, David Suter
Specifically, SDF includes three main parts: a deterministic sampling algorithm, a model hypothesis updating strategy and a novel model selection algorithm.
no code implementations • 4 Feb 2018 • Hanzi Wang, Guobao Xiao, Yan Yan, David Suter
We cast the task of geometric model fitting as a representative mode-seeking problem on hypergraphs.
no code implementations • 20 Jul 2016 • Guobao Xiao, Hanzi Wang, Yan Yan, David Suter
The feature appearances are beneficial to reduce the computational complexity for deterministic fitting methods.
no code implementations • 11 Jul 2016 • Guobao Xiao, Hanzi Wang, Taotao Lai, David Suter
The hypergraph, with large and "data-determined" degrees of hyperedges, can express the complex relationships between model hypotheses and data points.
no code implementations • ICCV 2015 • Hanzi Wang, Guobao Xiao, Yan Yan, David Suter
In addition to the mode seeking algorithm, MSH includes a similarity measure between vertices on the hypergraph and a weight-aware sampling technique.