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cs.CV2026
Inductive Convolution Nuclear Norm Minimization for Tensor Completion with Arbitrary Sampling
Wei Li, Yuyang Li, Kaile Du +2
The recently established Convolution Nuclear Norm Minimization (CNNM) addresses the problem of \textit{tensor completion with arbitrary sampling} (TCAS), which involves restoring a…
cs.CV2026
ZeroDiff++: Substantial Unseen Visual-semantic Correlation in Zero-shot Learning
Zihan Ye, Shreyank N Gowda, Kaile Du +2
Zero-shot Learning (ZSL) enables classifiers to recognize classes unseen during training, commonly via generative two stage methods: (1) learn visual semantic correlations from see…