Search Results for author:
Found 9 papers, 4 papers with code
DARNet: Dual-Attention Residual Network for Automatic Diagnosis of COVID-19 via CT Images
The ongoing global pandemic of Coronavirus Disease 2019 (COVID-19) poses a serious threat to public health and the economy.
Online Changepoint Detection on a Budget
In this paper, we are interested in changepoint detection algorithms which operate in an online setting in the sense that both its storage requirements and worst-case computational complexity per observation are independent of the number of previous observations.
Twin Weisfeiler-Lehman: High Expressive GNNs for Graph Classification
The expressive power of message passing GNNs is upper-bounded by Weisfeiler-Lehman (WL) test.
V-Cloak: Intelligibility-, Naturalness- & Timbre-Preserving Real-Time Voice Anonymization
Apart from the anonymity loss, we further incorporate the intelligibility loss and the psychoacoustics-based naturalness loss.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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H-DenseFormer: An Efficient Hybrid Densely Connected Transformer for Multimodal Tumor Segmentation
In this paper, we propose a hybrid densely connected network for tumor segmentation, named H-DenseFormer, which combines the representational power of the Convolutional Neural Network (CNN) and the Transformer structures.
Towards Privacy-Supporting Fall Detection via Deep Unsupervised RGB2Depth Adaptation
In this paper, we introduce a privacy-supporting solution that makes the RGB-trained model applicable in depth domain and utilizes depth data at test time for fall detection.
Seeing through the Mask: Multi-task Generative Mask Decoupling Face Recognition
Therefore, this paper proposes a Multi-task gEnerative mask dEcoupling face Recognition (MEER) network to jointly handle these two tasks, which can learn occlusionirrelevant and identity-related representation while achieving unmasked face synthesis.
CoSSegGaussians: Compact and Swift Scene Segmenting 3D Gaussians with Dual Feature Fusion
We propose Compact and Swift Segmenting 3D Gaussians(CoSSegGaussians), a method for compact 3D-consistent scene segmentation at fast rendering speed with only RGB images input.
PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models
However, LoRA approximates Delta W through the product of two matrices, A, initialized with Gaussian noise, and B, initialized with zeros, while PiSSA initializes A and B with principal singular values and vectors of the original matrix W. PiSSA can better approximate the outcomes of full-parameter fine-tuning at the beginning by changing the essential parts while freezing the "noisy" parts.
