71 citations · 172 across the 24 of their papers we have counts for
6 papers · 1 filter
Pixel-Level Change Detection Pseudo-Label Learning for Remote Sensing Change Captioning
Chenyang Liu, Keyan Chen, Zipeng Qi +3
The existing methods for Remote Sensing Image Change Captioning (RSICC) perform well in simple scenes but exhibit poorer performance in complex scenes. This limitation is primarily…
Layered Rendering Diffusion Model for Controllable Zero-Shot Image Synthesis
Zipeng Qi, Guoxi Huang, Chenyang Liu +1
This paper introduces innovative solutions to enhance spatial controllability in diffusion models reliant on text queries. We first introduce vision guidance as a foundational spat…
RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Model
Keyan Chen, Chenyang Liu, Hao Chen +4
Leveraging the extensive training data from SA-1B, the Segment Anything Model (SAM) demonstrates remarkable generalization and zero-shot capabilities. However, as a category-agnost…
Img2Vec: A Teacher of High Token-Diversity Helps Masked AutoEncoders
Heng Pan, Chenyang Liu, Wenxiao Wang +4
We present a pipeline of Image to Vector (Img2Vec) for masked image modeling (MIM) with deep features. To study which type of deep features is appropriate for MIM as a learning tar…
Implicit Ray-Transformers for Multi-view Remote Sensing Image Segmentation
Zipeng Qi, Hao Chen, Chenyang Liu +2
The mainstream CNN-based remote sensing (RS) image semantic segmentation approaches typically rely on massive labeled training data. Such a paradigm struggles with the problem of R…
Progressive Scale-aware Network for Remote sensing Image Change Captioning
Chenyang Liu, Jiajun Yang, Zipeng Qi +2
Remote sensing (RS) images contain numerous objects of different scales, which poses significant challenges for the RS image change captioning (RSICC) task to identify visual chang…