configs/loss/up_to_scale_loss.yaml

# Training Loss
train_criterion: "ConfAndExcludeTopNPercentPixelLoss(FactoredGeometryRegr3DPlusNormalGMLoss(RobustRegressionLoss(alpha=0.5, scaling_c=0.05), norm_mode='avg_dis', depth_type_for_loss='depth_along_ray', loss_in_log=True, flatten_across_image_only=True, compute_pairwise_relative_pose_loss=False, compute_world_frame_points_loss=True, apply_normal_and_gm_loss_to_synthetic_data_only=True, normal_loss_weight=3.0, gm_loss_weight=3.0), conf_alpha=0.2, top_n_percent=5, apply_to_real_data_only=True, conf_loss_set_indices=[0], exclude_loss_set_indices=[1, 2]) + 0.3 * NonAmbiguousMaskLoss(BCELoss())"
# Validation Loss
test_criterion: "ExcludeTopNPercentPixelLoss(FactoredGeometryRegr3DPlusNormalGMLoss(RobustRegressionLoss(alpha=0.5, scaling_c=0.05), norm_mode='avg_dis', depth_type_for_loss='depth_along_ray', loss_in_log=True, flatten_across_image_only=True, compute_pairwise_relative_pose_loss=False, compute_world_frame_points_loss=True, apply_normal_and_gm_loss_to_synthetic_data_only=True, normal_loss_weight=3.0, gm_loss_weight=3.0), top_n_percent=5, apply_to_real_data_only=True, loss_set_indices=[0, 1, 2]) + 0.3 * NonAmbiguousMaskLoss(BCELoss())"