Image Segmentation
Transformers
PyTorch
pixdlm
cvpr-2026
compute-transparency
reasoning-segmentation
uav
remote-sensing
vision-language
Instructions to use WhynotHug/PixDLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WhynotHug/PixDLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="WhynotHug/PixDLM")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WhynotHug/PixDLM", dtype="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: cc-by-nc-4.0
library_name: transformers
pipeline_tag: image-segmentation
tags:
- pixdlm
- cvpr-2026
- uav
- reasoning-segmentation
- remote-sensing
- compute-transparency
datasets:
- WhynotHug/DRSeg
PixDLM
This is the HuggingFace model card for PixDLM. The full source release is in the
repository root. See the root README.md for setup, data preparation,
evaluation, and training commands.
Links
Metrics
| Reasoning type | gIoU | cIoU |
|---|---|---|
| Attribute | 62.80 | 62.84 |
| Scene | 61.75 | 64.03 |
| Spatial | 62.51 | 62.80 |
Citation
@inproceedings{ke2026pixdlm,
title={PixDLM: A Dual-Path Multimodal Language Model for UAV Reasoning Segmentation},
author={Ke, Shuyan and Mei, Yifan and Wu, Changli and Zheng, Yonghan and Ji, Jiayi and Cao, Liujuan and Ji, Rongrong},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year={2026}
}