Dear Team,

Firstly, thank you for your incredible work on this paper. I am a graduate student implementing your method for an academic project, specifically to generate 3D models of jewelry (gold and diamond rings). I have been working on this for a few months, and while I greatly admire the technique, I am struggling to achieve realistic, high-quality results and would deeply appreciate your advice.

What I’ve Tried:

I am generating masks for the rings using 12 images.
I use Mast3R for pose estimation.
I’ve tried 10k, 20k, and 150k iterations but haven’t noticed a significant difference in quality.
I’ve adjusted the optimization parameters (details below), but the results worsened.

I’ve attached examples of my outputs for reference.

Despite these efforts, I haven’t been able to achieve realistic results. Given the nature of jewelry (reflective, detailed, and translucent), I wonder if I’m missing some crucial steps or adjustments.

Thank you so much for taking the time to help. Any advice would mean a lot, and I’d be happy to provide additional details if needed.

Optimization parameters

optimization_params = {
    'max_num_splats': 500_000_000,  # Maximum number of splats for densifying
    'iterations': 30_000,  # Total number of iterations for training
    'position_lr_init': 0.00030,  # Initial learning rate for position optimization
    'position_lr_final': 0.0000016,  # Final learning rate for position optimization
    'position_lr_delay_mult': 0.01,  # Delay multiplier for learning rate change
    'position_lr_max_steps': 30_000,  # Maximum number of steps for position optimization
    'feature_lr': 0.0030,  # Learning rate for feature optimization
    'opacity_lr': 0.01,  # Learning rate for opacity optimization
    'scaling_lr': 0.005,  # Learning rate for scaling optimization
    'rotation_lr': 0.001,  # Learning rate for rotation optimization
    'percent_dense': 0.10,  # Percentage of density to stop splitting/clone Gaussian
    'lambda_dssim': 1.0,  # Weight for DSSIM loss
    'lambda_silhouette': 0.02,  # Weight for silhouette loss
    'densification_interval': 50,  # Interval between densification steps
    'opacity_reset_interval': 1000,  # Interval for resetting opacity
    'remove_outliers_interval': 2000,  # Interval for removing outliers
    'densify_from_iter': 500,  # Start densification after this iteration
    'densify_until_iter': 20000,  # Stop densification after this iteration (60% of 10,000)
    'densify_grad_threshold': 0.00005,  # Gradient threshold for densification
    'start_sample_pseudo': 400000,  # Start sampling pseudo data (not used)
    'end_sample_pseudo': 1000000,  # End sampling pseudo data (not used)
    'sample_pseudo_interval': 10,  # Interval for pseudo-sampling (not used)
    'random_background': False,  # Flag to use random background in rendering
    'pose_iterations': 20000,  # Number of iterations for pose optimization
}

https://github.com/user-attachments/assets/151bb57f-ff3f-45d6-a013-a06c8c5de3e6

https://github.com/user-attachments/assets/a87df08b-dcc3-4905-b3b1-131cdc1058a3

chensjtu / GaussianObject

Help Needed for Generating High-Quality 3D Models #68

Optimization parameters