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Found 4 papers, 4 papers with code
Revisiting Few-Shot Object Detection with Vision-Language Models
In this work, we propose Foundational FSOD, a new benchmark protocol that evaluates detectors pre-trained on any external datasets and fine-tuned on K-shots per target class.
B-SMALL: A Bayesian Neural Network approach to Sparse Model-Agnostic Meta-Learning
We demonstrate the performance of B-MAML using classification and regression tasks, and highlight that training a sparsifying BNN using MAML indeed improves the parameter footprint of the model while performing at par or even outperforming the MAML approach.
REGroup: Rank-aggregating Ensemble of Generative Classifiers for Robust Predictions
Specifically, we devise an ensemble of these generative classifiers that rank-aggregates their predictions via a Borda count-based consensus.
C3VQG: Category Consistent Cyclic Visual Question Generation
In this paper, we try to exploit the different visual cues and concepts in an image to generate questions using a variational autoencoder (VAE) without ground-truth answers.
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