Search Results for author:
Found 6 papers, 2 papers with code
Fast Learning-based Registration of Sparse 3D Clinical Images
We present a learning-based registration method, SparseVM, that is more accurate and orders of magnitude faster than the most accurate clinical registration methods.
Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings
We present a probabilistic model that, given a single image of a completed painting, recurrently synthesizes steps of the painting process.
Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs
Interpretability methods aim to help users build trust in and understand the capabilities of machine learning models.
SizeGAN: Improving Size Representation in Clothing Catalogs
Online clothing catalogs lack diversity in body shape and garment size.
GIST: Generating Image-Specific Text for Fine-grained Object Classification
We demonstrate the utility of GIST by fine-tuning vision-language models on the image-and-generated-text pairs to learn an aligned vision-language representation space for improved classification.
Fine-Grained Image Classification
Image-text Classification
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GELDA: A generative language annotation framework to reveal visual biases in datasets
Results on real datasets show that GELDA can generate accurate and diverse visual attribute suggestions, and uncover biases such as confounding between class labels and background features.
