A Geometric-Transformation Feature-Adaptive Manifold Restoration Method for Open-Vocabulary Semantic Segmentation of Remote Sensing Images
cs.CV
Submitted: 2026-10-03
Updated: 2026-10-03
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- SAM 3: Segment Anything with Concepts
- ActiveSAM: Fast and Accurate Open-Vocabulary Semantic Segmentation with Frozen SAM 3
- Annotation-Free Open-Vocabulary Segmentation for Remote-Sensing Images
- ConInfer: Context-Aware Inference for Training-Free Open-Vocabulary Remote Sensing Segmentation
- InstructSAM: A Training-Free Framework for Instruction-Oriented Remote Sensing Object Recognition
- SegEarth-OV3: Exploring SAM 3 for Open-Vocabulary Semantic Segmentation in Remote Sensing Images
Related papers
- Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
- AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
- Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
- MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
- TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
- A Survey on Efficient Vision-Language-Action Models