67 citations · 221 across the 42 of their papers we have counts for
45 papers
T-MLA: A targeted multiscale log-exponential attack framework for neural image compression
Nikolay I. Kalmykov, Razan Dibo, Kaiyu Shen +4
Neural image compression (NIC) has become the state-of-the-art for rate-distortion performance, yet its security vulnerabilities remain significantly less understood than those of…
DeepNuParc: A Novel Deep Clustering Framework for Fine-scale Parcellation of Brain Nuclei Using Diffusion MRI Tractography
Haolin He, Ce Zhu, Le Zhang +9
Brain nuclei are clusters of anatomically distinct neurons that serve as important hubs for processing and relaying information in various neural circuits. Fine-scale parcellation…
Differentiable Low-computation Global Correlation Loss for Monotonicity Evaluation in Quality Assessment
Yipeng Liu, Qi Yang, Yiling Xu
In this paper, we propose a global monotonicity consistency training strategy for quality assessment, which includes a differentiable, low-computation monotonicity evaluation loss…
From Images to Point Clouds: An Efficient Solution for Cross-media Blind Quality Assessment without Annotated Training
Yipeng Liu, Qi Yang, Yujie Zhang +3
We present a novel quality assessment method which can predict the perceptual quality of point clouds from new scenes without available annotations by leveraging the rich prior kno…
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA
Lanlan Feng, Ce Zhu, Yipeng Liu +2
Robust tensor principal component analysis (RTPCA) aims to separate the low-rank and sparse components from multi-dimensional data, making it an essential technique in the signal p…
Fast randomized Kronecker tensor decomposition: algorithms and error analysis
Salman Ahmadi-Asl, Naeim Rezaeian, Andre L. F. de Almeida +1
This paper proposes fast randomized algorithms for computing the Kronecker Tensor Decomposition (KTD) by replacing the sequence of deterministic SVDs in the TTr1SVD framework with…