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Recent image generation models such as Stable Diffusion have exhibited an impressive ability to generate fairly realistic images starting from a simple text prompt.
Wordnet: A lexical database for English
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One-class SVM for learning in image retrieval
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The pascal visual object classes (VOC) challenge
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Torchvision the machine-vision package of torch
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Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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What makes ImageNet good for transfer learning?
Minyoung Huh, Pulkit Agrawal, and Alexei Efros · 2016
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Playing for data: Ground truth from computer games
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Learning from synthetic humans
Gul Varol, Javier Romero, Xavier Martin, Naureen Mahmood, Michael J Black, Ivan Laptev, and Cordelia Schmid · 2017
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Places: A 10 million image database for scene recognition
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Counterfactual image networks, 2018
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The iNaturalist species classification and detection dataset
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Zero-shot learning—a comprehensive evaluation of the good, the bad and the ugly
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Do better ImageNet models transfer better?
Scaling up visual and vision-language representation learning with noisy text supervision
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Simon Kornblith, Ting Chen, Honglak Lee, and Mohammad Norouzi · 2021
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Generative interventions for causal learning
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Learning transferable visual models from natural language supervision
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Zero-shot text-to-image generation
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Generative counterfactual introspection for explainable deep learning
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Continual lifelong learning with neural networks: A review
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PyTorch: An imperative style, high-performance deep learning library
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Classification accuracy score for conditional generative models
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Concept generalization in visual representation learning
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Image representations learned with unsupervised pre-training contain human-like biases
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Continual adaptation of visual representations via domain randomization and meta-learning
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Robust and generalizable visual representation learning via random convolutions
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Dataset condensation with gradient matching
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Easily accessible text-to-image generation amplifies demographic stereotypes at large scale
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