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title: InSAI Lab Profile
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<div align="center">
<img src="https://cdn-avatars.huggingface.co/v1/production/uploads/69d4baff8e85a8e1ae8370a5/qqeGpW3kQ8GVDcazES1nW.png" width="120px" alt="InSAI Lab Logo" />
# Integrated Sensing and Assistive Intelligence (InSAI) Lab
### School of AI and Robotics, Hunan University (HNU)
<p align="center">
<a href="https://insailab.org"><img src="https://img.shields.io/badge/Official-Website-blue?style=flat-square&logo=googlechrome" /></a>
<a href="https://github.com/InSAI-Lab"><img src="https://img.shields.io/badge/GitHub-InSAI--Lab-181717?style=flat-square&logo=github" /></a>
<a href="https://huggingface.co/InSAI-Lab"><img src="https://img.shields.io/badge/HuggingFace-InSAI--Lab-FFD21E?style=flat-square&logo=huggingface" /></a>
<a href="mailto:jiamingzhang@hnu.edu.cn"><img src="https://img.shields.io/badge/Email-Contact_Us-red?style=flat-square&logo=gmail" /></a>
</p>
*"Building a utopia where integrated sensing systems empower and enhance human capabilities, especially benefiting people with disabilities."*
</div>
---
## 🎯 About InSAI Lab
The **InSAI** (pronounced like *"Insight"*) Lab operates within the **School of AI and Robotics at Hunan University**.
Our mission is to merge interdisciplinary fields — including **computer vision, robotics, intelligent transportation systems, assistive technologies, and human-computer interaction (HCI)** — to develop deployable **Assistive Intelligence**.
### Core Research Directions
- 🌐 **Multimodal Perception & Scene Understanding:** Vision-Language Modeling, 2D/3D Vision, and sensor fusion in complex, adverse real-world environments.
- 🚗 **Autonomous Systems & Panoramic Vision:** Semantic Mapping, Panoramic Sensing, Distortion-aware Transformers, and Bird’s-Eye-View (BEV) perception.
- 🤖 **Embodied Intelligence:** Perception, navigation, and decision-making linking foundation models with robotic action, including Sim2Real adaptation.
- ♿ **Assistive Technologies:** Wearable assistive systems, navigation aids, and accessible interfaces designed around human capabilities.
- 🧠 **Brain-Computer Interface & Document Understanding:** Cognitive state sensing, assistive BCI, and intelligent layout/reading assistance.
---
## 🌟 Featured Collections & Open-Source Suites
### 1. [📚 Collection: DeLiVER & CMNeXt (CVPR 2023)](https://huggingface.co/collections/InSAI-Lab/deliver-and-cmnext-cvpr-2023-6ac37817fd1ef3e1096e970e)
> **Delivering Arbitrary-Modal Semantic Segmentation**
A unified benchmark and cross-modal suite scaling dynamically across **1 to 81 modalities** (Depth, LiDAR, Events, Multi-Views, RGB) under 4 severe weather conditions and 5 sensor failure corner cases.
| Resource | Hugging Face Repository | Description |
| :--- | :--- | :--- |
| 📦 **Dataset** | [`InSAI-Lab/DELIVER`](https://huggingface.co/datasets/InSAI-Lab/DELIVER) | Full multimodal dataset package (12.22 GB) |
| 🤖 **Model Zoo** | [`InSAI-Lab/CMNeXt`](https://huggingface.co/InSAI-Lab/CMNeXt) | 37 trained checkpoints covering DELIVER, KITTI-360, MFNet, NYU Depth V2, UrbanLF, MCubeS, and SegFormer/Swin backbones |
| 📄 **Paper** | [arXiv:2303.01480](https://arxiv.org/abs/2303.01480) | CVPR 2023 Paper |
```bash
# Quick download via Hugging Face CLI
hf download InSAI-Lab/DELIVER DELIVER.tar.gz --type dataset --local-dir ./data
hf download InSAI-Lab/CMNeXt --local-dir ./checkpoints
```
---
### 2. [📚 Collection: Trans4PASS & SynPASS (CVPR 2022)](https://huggingface.co/collections/InSAI-Lab/trans4pass-and-synpass-cvpr-2022-6ac378180330fc67aeeedff3)
> **Transformers for Panoramic Semantic Segmentation & Domain Adaptation**
Distortion-aware Vision Transformers tailored for 360° panoramic cameras and omnidirectional scene understanding, featuring the 9,080-frame SynPASS benchmark.
| Resource | Hugging Face Repository | Description |
| :--- | :--- | :--- |
| 📦 **Dataset** | [`InSAI-Lab/SynPASS`](https://huggingface.co/datasets/InSAI-Lab/SynPASS) | 9,080 high-res panoramic semantic segmentation benchmark (4.79 GB) |
| 🤖 **Model Zoo** | [`InSAI-Lab/Trans4PASS`](https://huggingface.co/InSAI-Lab/Trans4PASS) | 40 checkpoints across Cityscapes, Stanford2D3D, Structured3D, and MPA domain adaptation snapshots |
| 📄 **Papers** | [arXiv:2203.01452](https://arxiv.org/abs/2203.01452) / [arXiv:2207.11860](https://arxiv.org/abs/2207.11860) | CVPR 2022 & arXiv Preprints |
```bash
# Quick download via Hugging Face CLI
hf download InSAI-Lab/SynPASS SynPASS.tar.gz --type dataset --local-dir ./datasets
hf download InSAI-Lab/Trans4PASS --local-dir ./workdirs
```
---
## 🔬 Recent Selected Publications
- **IEEE T-PAMI 2026:** *OneBEV++: Towards Unifying Bird’s-Eye-View Semantic Mapping with Panoramas*
- **CVPR 2026:** *More than the Sum: Panorama-Language Models for Adverse Omni-Scenes*
- **ICML 2026:** *Position: Assistive Agents Need Accessibility Alignment*
- **BMVC 2026:** *X²Localizer: Cross-grained Alignment for Progressive Cross-view Video Geo-localization*
- **CVPR 2023:** *Delivering Arbitrary-Modal Semantic Segmentation (DeLiVER & CMNeXt)*
- **CVPR 2022:** *Bending Reality: Distortion-aware Transformers for Adapting to Panoramic Semantic Segmentation (Trans4PASS)*
---
## 🤝 Connect & Collaborate
- 🌐 **Official Website:** [https://insailab.org](https://insailab.org)
- 💻 **GitHub Organization:** [https://github.com/InSAI-Lab](https://github.com/InSAI-Lab)
- 📬 **Recruitment & Inquiries:** [jiamingzhang@hnu.edu.cn](mailto:jiamingzhang@hnu.edu.cn)
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