Comments (1)
Hello,
You are right that it's a design choice to remove the randomness from the sampling process. However, only by this means the predictions are not as consistent as we expected, which is the main reason for introducing the ensemble.
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Related Issues (20)
- Is code from the Bas-relief available
- Why set NaN depth values to zero on preprocessing? HOT 1
- Request for vkitti_val.tar and vkitti_vis.tar files HOT 1
- How to Manage the Large Hypersim Dataset for Reproduction? HOT 3
- ask for LCM distillation code HOT 2
- Low-Rank(LoRA) training of Marigold
- Multi-GPU Training HOT 1
- Clarification Needed: Training and Inference Pipeline HOT 4
- Any reason for not using vae.std to generate RGB latent? HOT 1
- do you plan to release better and more accurate models for this original marigold? HOT 1
- The purpose of using v_prediction as the target? HOT 1
- where can I get the "output/marigold_base/checkpoint/latest" HOT 1
- The demo 3D looks ok but not match with the predicted depth image HOT 1
- How to organize the vkitti data HOT 1
- train the model on my custom dataset HOT 1
- Unusual slow training speed HOT 6
- About some problems that arise during training HOT 9
- issue with reproducing results in the paper HOT 1
- Is it possible to train the model by feeding it rgb images + 8-bit relative depth maps ? HOT 1
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