Performance Optimization Solutions
Diffuman4D realizes real-time rendering through 4DGS technology and hardware acceleration. To further improve the performance, the following measures can be taken: firstly, use the -low_mem parameter in the code to reduce the video memory usage in the modeling stage; secondly, adjust the lod_level parameter in config.yaml to control the detail level during rendering; and it is also recommended to convert the final model to the lightweight PLY format.
concrete operation
- Add the -compress argument when reconstructing the model: python scripts/reconstruct_4dgs.py -compress
- Set frame_rate=30 in render_example.py to maintain smoothness
- Super-resolution rendering using NVIDIA's DLSS technology
Hardware Recommendations
The best configuration is RTX 3080 and above graphics card with 12GB or more video memory. If you have limited hardware, you can adjust the resolution parameter to 720p in data/input/config.yaml to reduce the demand.
This answer comes from the articleDiffuman4D: Generating High-Fidelity 4D Human Body Views from Sparse VideoThe
