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Found 4 papers, 2 papers with code
SYNAuG: Exploiting Synthetic Data for Data Imbalance Problems
We live in an era of data floods, and deep neural networks play a pivotal role in this moment.
DFlow: Learning to Synthesize Better Optical Flow Datasets via a Differentiable Pipeline
Comprehensive studies of synthetic optical flow datasets have attempted to reveal what properties lead to accuracy improvement in learning-based optical flow estimation.
Scratching Visual Transformer's Back with Uniform Attention
We observe that the inclusion of CB reduces the degree of density in the original attention maps and increases both the capacity and generalizability of the ViT models.
FedPara: Low-Rank Hadamard Product for Communication-Efficient Federated Learning
We show that pFedPara outperforms competing personalized FL methods with more than three times fewer parameters.
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