Update README.md

README.md

@@ -291,6 +291,7 @@ Speed is related to the hardware spec (e.g. CPU, GPU, RAM, etc), so it is hard t
 - **[MCN-DRM]** Zheng, Z., et al. (2020). Multi-resolution Cascaded Network with Depth-similar Residual Module for Real-time Semantic Segmentation on RGB-D Images.  IEEE International Conference on Networking, Sensing and Control (ICNSC). [[Paper]](https://ieeexplore.ieee.org/document/9238079) [Code]
 - **[CANet]** Zhou H., et al. (2020). RGB-D Co-attention Network for Semantic Segmentation. Asian Conference on Computer Vision. [[Paper]](https://openaccess.thecvf.com/content/ACCV2020/papers/Zhou_RGB-D_Co-attention_Network_for_Semantic_Segmentation_ACCV_2020_paper.pdf) [Code]
 - **[CEN]** Wang, Y., et al. (2020). Deep Multimodal Fusion by Channel Exchanging. 34th Conference on Neural Information Processing Systems [[Paper]](https://arxiv.org/pdf/arXiv:2011.05005.pdf) [[Code]](https://github.com/yikaiw/CEN)
+- **[Z-ACN]** Wu, Z., et al. (2020). Depth-Adapted CNN for RGB-D cameras. Asian Conference on Computer Vision. [[Paper]](https://arxiv.org/pdf/2009.09976.pdf)
 - **[AdapNet++]** Valada, A., et al. (2020). Self-Supervised Model Adaptation for Multimodal Semantic Segmentation. International Journal of Computer Vision [[Paper]](https://arxiv.org/pdf/arXiv:1808.03833.pdf) [[Code]](https://github.com/DeepSceneSeg)
 - **[ESANet]** Seichter, D., et al. (2021). Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis. IEEE International Conference on Robotics and Automation. [[Paper]](https://arxiv.org/pdf/arXiv:2011.06961.pdf) [[Code]](https://github.com/TUI-NICR/ESANet)
 - **[LWM]** Gu, Z., et al. (2021). Hard Pixel Mining for Depth Privileged Semantic Segmentation. IEEE Transactions on Multimedia. [[Paper]](https://arxiv.org/pdf/1906.11437.pdf) [Code]