NCA-GENM Exam Dumps | You're training a multimodal model to generate 3D models from text descriptions. The models are evaluated

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Question 60/192

You're training a multimodal model to generate 3D models from text descriptions. The models are evaluated using Intersection over Union (IOU) between the generated and ground truth 3D models. During evaluation, you observe perfect IOU scores on some samples, but visual inspection reveals significant discrepancies. What is the MOST likely cause for this, and what can be done to correct the process?

A. The model is overfitting, resulting in near-perfect reconstruction of a subset of training samples. Reduce the model's capacity.

B. There is a data leakage issue, where some of the test data is present in the training data. Ensure that training and test data are completely disjoint.

C. The IOU calculation is being performed incorrectly, or there is a bug in the evaluation code. Verify the IOU implementation.

D. The text descriptions are too simple. Use more complex text prompts to prevent overfitting.

E. IOU is an inherently flawed metric for evaluating 3D models and needs to be replaced by Chamfer distance.

Correct Answer: C

Perfect IOU scores with visual discrepancies strongly suggest a problem with the IOU calculation itself (C). Data leakage (B) or overfitting (A) are possibilities, but a bug in the IOU implementation is more likely given the perfect scores. Text complexity (D) doesn't explain perfect scores with visual errors. IOU is a valid metric, and it could be supplemented with chamfer distance, but if IOU gives perfect scores with visual discrepancies, then the immediate action needed is to verify IOU implementation. Thus, the best option is C.

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