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Found 6 papers, 3 papers with code
Count What You Want: Exemplar Identification and Few-shot Counting of Human Actions in the Wild
To develop and evaluate our approach, we introduce a diverse and realistic dataset consisting of real-world data from 37 subjects and 50 action categories, encompassing both sensor and audio data.
Interactive Class-Agnostic Object Counting
The user can provide feedback by selecting a region with obvious counting errors and specifying the range for the estimated number of objects within it.
Machine-Learning Compression for Particle Physics Discoveries
In collider-based particle and nuclear physics experiments, data are produced at such extreme rates that only a subset can be recorded for later analysis.
The Devil is in the Labels: Noisy Label Correction for Robust Scene Graph Generation
Then, in Pos-NSD, we use a clustering-based algorithm to divide all positive samples into multiple sets, and treat the samples in the noisiest set as noisy positive samples.
From the Greene--Wu Convolution to Gradient Estimation over Riemannian Manifolds
Over a complete Riemannian manifold of finite dimension, Greene and Wu introduced a convolution, known as Greene-Wu (GW) convolution.
