1 code implementation • 14 Apr 2024 • Chengxi Han, Chen Wu, HaoNan Guo, Meiqi Hu, Jiepan Li, Hongruixuan Chen
The rapid advancement of automated artificial intelligence algorithms and remote sensing instruments has benefited change detection (CD) tasks.
Ranked #1 on Change Detection on LEVIR+
2 code implementations • 14 Apr 2024 • Chengxi Han, Chen Wu, HaoNan Guo, Meiqi Hu, Hongruixuan Chen
Benefiting from the developments in deep learning technology, deep-learning-based algorithms employing automatic feature extraction have achieved remarkable performance on the change detection (CD) task.
Ranked #1 on Change Detection on GoogleGZ-CD
1 code implementation • 20 Mar 2024 • Di Wang, Jing Zhang, Minqiang Xu, Lin Liu, Dongsheng Wang, Erzhong Gao, Chengxi Han, HaoNan Guo, Bo Du, DaCheng Tao, Liangpei Zhang
However, transferring the pretrained models to downstream tasks may encounter task discrepancy due to their formulation of pretraining as image classification or object discrimination tasks.
Ranked #1 on Semantic Segmentation on SpaceNet 1 (using extra training data)
Aerial Scene Classification Building change detection for remote sensing images +12
1 code implementation • 17 Jan 2024 • HaoNan Guo, Xin Su, Chen Wu, Bo Du, Liangpei Zhang, Deren Li
Recently, the flourishing large language models(LLM), especially ChatGPT, have shown exceptional performance in language understanding, reasoning, and interaction, attracting users and researchers from multiple fields and domains.
no code implementations • 28 Aug 2023 • HaoNan Guo, Xin Su, Chen Wu, Bo Du, Liangpei Zhang
These CD methods, however, still perform far from satisfactorily as we observe that 1) deep encoder layers focus on irrelevant background regions and 2) the models' confidence in the change regions is inconsistent at different decoder stages.
no code implementations • 23 Jul 2023 • HaoNan Guo, Xin Su, Chen Wu, Bo Du, Liangpei Zhang
Compared with many existing methods that train each task individually, the proposed collaborative extraction method can utilize the complementary advantages between buildings and roads by the proposed inter-task and inter-scale feature interactions, and automatically select the optimal reception field for different tasks.
1 code implementation • 23 Jul 2023 • HaoNan Guo, Bo Du, Chen Wu, Xin Su, Liangpei Zhang
The efficacy of building footprint segmentation from remotely sensed images has been hindered by model transfer effectiveness.
1 code implementation • 23 Jul 2023 • HaoNan Guo, Bo Du, Chen Wu, Chengxi Han, Liangpei Zhang
To address these issues, we complement the strong temporal modeling ability of metric learning with the prominent fitting ability of segmentation and propose a deep change feature learning (DeepCL) framework for robust and explainable CD.
no code implementations • 26 Jun 2020 • Chen Wu, Yinong Guo, HaoNan Guo, Jingwen Yuan, Lixiang Ru, Hongruixuan Chen, Bo Du, Liangpei Zhang
The significant reduction and recovery of traffic density indicates that the lockdown policy in Wuhan show effectiveness in controlling human transmission inside the city, and the city returned to normal after lockdown lift.