most citedAdapting Vision Foundation Models for Robust Cloud Segmentation in Remote Sensing Images

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Butter: Frequency Consistency and Hierarchical Fusion for Autonomous Driving Object Detection

Xiaojian Lin, Wenxin Zhang, Yuchu Jiang +7

Hierarchical feature representations play a pivotal role in computer vision, particularly in object detection for autonomous driving. Multi-level semantic understanding is crucial…

cs.CV2025

StickMotion: Generating 3D Human Motions by Drawing a Stickman

Tao Wang, Zhihua Wu, Qiaozhi He +6

Text-to-motion generation, which translates textual descriptions into human motions, has been challenging in accurately capturing detailed user-imagined motions from simple text in…

cs.CV2025

DiffBrush:Just Painting the Art by Your Hands

Jiaming Chu, Lei Jin, Tao Wang +2

The rapid development of image generation and editing algorithms in recent years has enabled ordinary user to produce realistic images. However, the current AI painting ecosystem p…

cs.CV20241 cited

Adapting Vision Foundation Models for Robust Cloud Segmentation in Remote Sensing Images

Xuechao Zou, Shun Zhang, Kai Li +5

Cloud segmentation is a critical challenge in remote sensing image interpretation, as its accuracy directly impacts the effectiveness of subsequent data processing and analysis. Re…

cs.CV2024

DriveWorld: 4D Pre-trained Scene Understanding via World Models for Autonomous Driving

Chen Min, Dawei Zhao, Liang Xiao +10

Vision-centric autonomous driving has recently raised wide attention due to its lower cost. Pre-training is essential for extracting a universal representation. However, current vi…