Neural-Guided RANSAC for Estimating Epipolar Geometry [Data]
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Pre-computed sparse feature correspondences for pairs of images (outdoor and indoor) to reproduce the experiments described in our paper, particularly to train and evaluate NG-RANSAC.For more information, also see the code documentation: https://github.com/vislearn/ngransa' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Computer Vision","Machine Learning","Neural networks (Computer science)"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Pre-computed sparse feature correspondences for pairs of images (outdoor and indoor) to reproduce the experiments described in our paper, particularly to train and evaluate NG-RANSAC.For more information, also see the code documentation: https://github.com/vislearn/ngransa' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Pre-computed sparse feature correspondences for pairs of images (outdoor and indoor) to reproduce the experiments described in our paper, particularly to train and evaluate NG-RANSAC.For more information, also see the code documentation: https://github.com/vislearn/ngransa
Computer Vision; Machine Learning; Neural networks (Computer science)