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[ICCV 2025] LangScene-X: Reconstruct Generalizable 3D Language-Embedded Scenes with TriMap Video Diffusion
| Date | Stars |
|---|---|
| 2026-07-24 | 302 |
| 2026-07-25 | 302 |
| 2026-07-28 | 302 |
| 2026-07-30 | 302 |
| 2026-08-06 | 302 |
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<div align="center">
# ✨LangScene-X: Reconstruct Generalizable 3D Language-Embedded Scenes with TriMap Video Diffusion✨
<p align="center">
<a href="https://liuff19.github.io/">Fangfu Liu</a><sup>1</sup>,
<a href="https://lifuguan.github.io/">Hao Li</a><sup>2</sup>,
<a href="https://github.com/chijw">Jiawei Chi</a><sup>1</sup>,
<a href="https://hanyang-21.github.io/">Hanyang Wang</a><sup>1,3</sup>,
<a href="https://github.com/liuff19/LangScene-X">Minghui Yang</a><sup>3</sup>,
<a href="https://github.com/liuff19/LangScene-X">Fudong Wang</a><sup>3</sup>,
<a href="https://duanyueqi.github.io/">Yueqi Duan</a><sup>1</sup>
<br>
<sup>1</sup>Tsinghua University, <sup>2</sup>NTU, <sup>3</sup>Ant Group
</p>
<h3 align="center">ICCV 2025 🔥</h3>
<a href="https://arxiv.org/abs/2507.02813"><img src='https://img.shields.io/badge/arXiv-2507.02813-b31b1b.svg'></a>
<a href="https://liuff19.github.io/LangScene-X"><img src='https://img.shields.io/badge/Project-Page-Green'></a>
<a href="https://huggingface.co/chijw/LangScene-X"><img src='https://img.shields.io/badge/LangSceneX-huggingface-yellow'></a>
<a><img src='https://img.shields.io/badge/License-MIT-blue'></a>
</div>
**LangScene-X:** We propose LangScene-X, a unified model that generates RGB, segmentation map, and normal map, enabling to reconstruct 3D field from sparse views input.
## 📢 News
- 🔥 [04/07/2025] We release "LangScene-X: Reconstruct Generalizable 3D Language-Embedded Scenes with TriMap Video Diffusion". Check our [project page](https://liuff19.github.io/LangScene-X) and [arXiv paper](https://arxiv.org/abs/2507.02813).
## 🌟 Pipeline
Pipeline of LangScene-X. Our model is composed of a TriMap Video Diffusion model which generates RGB, segmentation map, and normal map videos, an Auto Encoder that compresses the language feature, and a field constructor that reconstructs 3DGS from the generated videos.
## 🎨 Video Demos from TriMap Video Diffusion
https://github.com/user-attachments/assets/55346d53-eb04-490e-bb70-64555e97e040
https://github.com/user-attachments/assets/d6eb28b9-2af8-49a7-bb8b-0d4cba7843a5
https://github.com/user-attachments/assets/396f11ef-85dc-41de-882e-e249c25b9961
## ⚙️ Setup
### 1. Clone Repository
```bash
git clone https://github.com/liuff19/LangScene-X.git
cd LangScene-X
```
### 2. Environment Setup
1. **Create conda environment**
```bash
conda create -n langscenex python=3.10 -y
conda activate langscenex
```
2. **Install dependencies**
```bash
conda install pytorch torchvision -c pytorch -y
pip install -e field_construction/submodules/simple-knn
pip install -e field_construction/submodules/diff-langsurf-rasterizer
pip install -e auto-seg/submodules/segment-anything-1
pip install -e auto-seg/submodules/segment-anything-2
pip install -r requirements.txt
```
### 3. Model Checkpoints
The checkpoints of SAM, SAM2 and fine-tuned CogVideoX can be downloaded from our [huggingface repository](https://huggingface.co/chijw/LangScene-X).
## 💻Running
### Quick Start
You can start quickly by running the following scripts:
```bash
chmod +x quick_start.sh
./quick_start.sh <first_rgb_image_path> <last_rgb_image_path>
```
### Render
Run the following command to render from the reconstructed 3DGS field:
```bash
python entry_point.py \
pipeline.rgb_video_path="does/not/matter" \
pipeline.normal_video_path="does/not/matter" \
pipeline.seg_video_path="does/not/matter" \
pipeline.data_path="does/not/matter" \
gaussian.dataset.source_path="does/not/matter" \
gaussian.dataset.model_path="output/path" \
pipeline.selection=False \
gaussian.opt.max_geo_iter=1500 \
gaussian.opt.normal_optim=True \
gaussian.opt.optim_pose=True \
pipeline.skip_video_process=True \
pipeline.skip_lang_feature_extraction=True \
pipeline.mode="rExcerpt of 5,229 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:e1846f524326fe8b, topic:3d-reconstruction
matched fp:e1846f524326fe8b, topic:video-generation