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Found 5 papers, 4 papers with code
Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient
The large model serves as the 'drafter', specializing in generating low-frequency content at smaller scales, while the smaller model serves as the 'refiner', solely focusing on predicting high-frequency details at larger scales.
Heavy Labels Out! Dataset Distillation with Label Space Lightening
Extensive experiments demonstrate that with only about 0. 003% of the original storage required for a complete set of soft labels, we achieve comparable performance to current state-of-the-art dataset distillation methods on large-scale datasets.
AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising
To address this, we introduce AsyncDiff, a universal and plug-and-play acceleration scheme that enables model parallelism across multiple devices.
SlimSAM: 0.1% Data Makes Segment Anything Slim
To address this challenging trade-off, we introduce SlimSAM, a novel data-efficient SAM compression method that achieves superior performance with extremely less training data.
Lens-to-lens bokeh effect transformation. NTIRE 2023 challenge report
We present the new Bokeh Effect Transformation Dataset (BETD), and review the proposed solutions for this novel task at the NTIRE 2023 Bokeh Effect Transformation Challenge.
