most citedLessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification

7 citations · 9 across the 3 of their papers we have counts for

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cs.CV2023★ 5 cited

EditVal: Benchmarking Diffusion Based Text-Guided Image Editing Methods

Samyadeep Basu, Mehrdad Saberi, Shweta Bhardwaj +5

A plethora of text-guided image editing methods have recently been developed by leveraging the impressive capabilities of large-scale diffusion-based generative models such as Imag…

cs.CV2023★ 2 cited

Strong Baselines for Parameter Efficient Few-Shot Fine-tuning

Samyadeep Basu, Daniela Massiceti, Shell Xu Hu +1

Few-shot classification (FSC) entails learning novel classes given only a few examples per class after a pre-training (or meta-training) phase on a set of base classes. Recent work…