Update README.md

README.md

@@ -1,3 +1,21 @@
+---
+license: cc-by-nc-4.0
+language:
+- en
+tags:
+- novel view synthesis
+- dynamic scene novel view segmentation
+- 3d segmentation
+- neural radiance fields
+- gaussian splatting
+datasets:
+- hypernerf
+- nerf-ds
+- neural-3d-video
+- google-immersive
+- technicolor-light-field
+---
+
 # Mask-Benchmark Dataset
 
 This repository contains the dynamic scene novel-view segmentation benchmarks used in the paper "SADG: Segment Any Dynamic Gaussian Without Object Trackers" [1]. The benchmarks are designed for evaluating segmentation performance in dynamic novel view synthesis across various datasets.
@@ -12,3 +30,13 @@ The Mask-Benchmark dataset provides ground truth segmentation masks for multiple
 - Technicolor Light Field (Dataset and Pipeline for Multi-View Light-Field Video, CVPRW 2017)
 
 These benchmarks allow for quantitative evaluation of segmentation accuracy (mIoU and mAcc) in novel view synthesis for dynamic scenes, which was previously lacking in the field.
+
+## BibTex
+```
+@article{li2024sadg,
+    title={SADG: Segment Any Dynamic Gaussian Without Object Trackers},
+    author={Li, Yun-Jin and Gladkova, Mariia and Xia, Yan and Cremers, Daniel},
+    journal={arXiv preprint arXiv:2411.19290},
+    year={2024}
+}
+```