[NeurIPS 2024 Spotlight]"LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPS", Zhiwen Fan, Kevin Wang, Kairun Wen, Zehao Zhu, Dejia Xu, Zhangyang Wang
First, I would like to thank you for the amazing work that you have done and the impressive ideas that you proposed to compress the 3D-GS model while maintaining reasonably good quality.
I was exploring the point_cloud.ply file that you shared here for the room model. It seems that the file size is about 77 MB. While in the current version (v4) of your paper, in Table 2, it is mentioned that the same model has a size of about 20 MB.
Similar information is also mentioned in Table 4:
My understanding from the tables is that, the model that you shared are only optimized via Pruning & Recovery and SH Distillation but they are not VecTree quantized. Could you please verify if that is correct? And if yes, could you please share the model where you applied all the three optimization steps?
Dear Authors,
First, I would like to thank you for the amazing work that you have done and the impressive ideas that you proposed to compress the 3D-GS model while maintaining reasonably good quality.
I was exploring the
point_cloud.plyfile that you shared here for the room model. It seems that the file size is about 77 MB. While in the current version (v4) of your paper, in Table 2, it is mentioned that the same model has a size of about 20 MB.Similar information is also mentioned in Table 4:
My understanding from the tables is that, the model that you shared are only optimized via Pruning & Recovery and SH Distillation but they are not VecTree quantized. Could you please verify if that is correct? And if yes, could you please share the model where you applied all the three optimization steps?