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Found 5 papers, 1 papers with code
VastGaussian: Vast 3D Gaussians for Large Scene Reconstruction
Existing NeRF-based methods for large scene reconstruction often have limitations in visual quality and rendering speed.
SELC: Self-Ensemble Label Correction Improves Learning with Noisy Labels
We look deeper into the memorization behavior in training with noisy labels and observe that the network outputs are reliable in the early stage.
Confidence Adaptive Regularization for Deep Learning with Noisy Labels
Recent studies on the memorization effects of deep neural networks on noisy labels show that the networks first fit the correctly-labeled training samples before memorizing the mislabeled samples.
Ranked #28 on
Image Classification
on mini WebVision 1.0
Co-matching: Combating Noisy Labels by Augmentation Anchoring
We then update two networks simultaneously by selecting small-loss instances to minimize both unsupervised matching loss (i. e., measure the consistency of the two networks) and supervised classification loss (i. e. measure the classification performance).
CLTA: Contents and Length-based Temporal Attention for Few-shot Action Recognition
Few-shot action recognition has attracted increasing attention due to the difficulty in acquiring the properly labelled training samples.
