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Found 4 papers, 1 papers with code
Learning with Diversity: Self-Expanded Equalization for Better Generalized Deep Metric Learning
Most existing DML methods focus on improving the model robustness against category shift to keep the performance on unseen categories.
Understanding and Improving Early Stopping for Learning with Noisy Labels
Instead of the early stopping, which trains a whole DNN all at once, we initially train former DNN layers by optimizing the DNN with a relatively large number of epochs.
Ranked #8 on
Learning with noisy labels
on CIFAR-10N-Aggregate
Progressive Domain-Independent Feature Decomposition Network for Zero-Shot Sketch-Based Image Retrieval
Specifically, with the supervision of original semantic knowledge, PDFD decomposes visual features into domain features and semantic ones, and then the semantic features are projected into common space as retrieval features for ZS-SBIR.
Unsupervised Deep Generative Adversarial Hashing Network
HashGAN consists of three networks, a generator, a discriminator and an encoder.
