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Dtl: Disentangled transfer learning for visual recognition
When pre-trained models become rapidly larger, the cost of fine-tuning on downstream tasks
steadily increases, too. To economically fine-tune these models, parameter-efficient transfer …
steadily increases, too. To economically fine-tune these models, parameter-efficient transfer …
Diffult: How to make diffusion model useful for long-tail recognition
This paper proposes a new pipeline for long-tail (LT) recognition. Instead of re-weighting or
re-sampling, we utilize the long-tailed dataset itself to generate a balanced proxy that can be …
re-sampling, we utilize the long-tailed dataset itself to generate a balanced proxy that can be …
DiffuLT: Diffusion for Long-tail Recognition Without External Knowledge
This paper introduces a novel pipeline for long-tail (LT) recognition that diverges from
conventional strategies. Instead, it leverages the long-tailed dataset itself to generate a …
conventional strategies. Instead, it leverages the long-tailed dataset itself to generate a …
Coarse is better? a new pipeline towards self-supervised learning with uncurated images
Most self-supervised learning (SSL) methods often work on curated datasets where the
object-centric assumption holds. This assumption breaks down in uncurated images …
object-centric assumption holds. This assumption breaks down in uncurated images …