Search Results for author:
Found 25 papers, 15 papers with code
Weakly-Supervised Crowd Counting Learns from Sorting rather than Locations
We propose a soft-label sorting network along with the counting network, which sorts the given images by their crowd numbers.
Adapting pretrained speech model for Mandarin lyrics transcription and alignment
With the use of data augmentation and source separation model, results show that the proposed method achieves a character error rate of less than 18% on a Mandarin polyphonic dataset for lyrics transcription, and a mean absolute error of 0. 071 seconds for lyrics alignment.
Enhancing Motor Imagery Decoding in Brain Computer Interfaces using Riemann Tangent Space Mapping and Cross Frequency Coupling
Objective: Motor Imagery (MI) serves as a crucial experimental paradigm within the realm of Brain Computer Interfaces (BCIs), aiming to decoding motor intentions from electroencephalogram (EEG) signals.
Popularity, face and voice: Predicting and interpreting livestreamers' retail performance using machine learning techniques
Livestreaming commerce, a hybrid of e-commerce and self-media, has expanded the broad spectrum of traditional sales performance determinants.
Self-supervised Cross-view Representation Reconstruction for Change Captioning
Change captioning aims to describe the difference between a pair of similar images.
A Phoneme-Informed Neural Network Model for Note-Level Singing Transcription
Note-level automatic music transcription is one of the most representative music information retrieval (MIR) tasks and has been studied for various instruments to understand music.
Neighborhood Contrastive Transformer for Change Captioning
Change captioning is to describe the semantic change between a pair of similar images in natural language.
ReAssigner: A Plug-and-Play Virtual Machine Scheduling Intensifier for Heterogeneous Requests
With the rapid development of cloud computing, virtual machine scheduling has become one of the most important but challenging issues for the cloud computing community, especially for practical heterogeneous request sequences.
Modeling Temporal Concept Receptive Field Dynamically for Untrimmed Video Analysis
Based on TDC, we propose the temporal dynamic concept modeling network (TDCMN) to learn an accurate and complete concept representation for efficient untrimmed video analysis.
Self-Regulated Learning for Egocentric Video Activity Anticipation
Future activity anticipation is a challenging problem in egocentric vision.
Actions Speak Louder than Listening: Evaluating Music Style Transfer based on Editing Experience
In this paper, we propose an editing test to evaluate users' editing experience of music generation models in a systematic way.
ReconVAT: A Semi-Supervised Automatic Music Transcription Framework for Low-Resource Real-World Data
Most of the current supervised automatic music transcription (AMT) models lack the ability to generalize.
Omnizart: A General Toolbox for Automatic Music Transcription
We present and release Omnizart, a new Python library that provides a streamlined solution to automatic music transcription (AMT).
SE-Harris and eSUSAN: Asynchronous Event-Based Corner Detection Using Megapixel Resolution CeleX-V Camera
The proposed eSUSAN extracts the univalue segment assimilating nucleus from the circle kernel based on the similarity across timestamps and distinguishes corner events by the number of pixels in the nucleus area.
Rethinking Graph Neural Architecture Search from Message-passing
Inspired by the strong searching capability of neural architecture search (NAS) in CNN, this paper proposes Graph Neural Architecture Search (GNAS) with novel-designed search space.
Crossing You in Style: Cross-modal Style Transfer from Music to Visual Arts
Its major difference from the traditional image style transfer problem is that the style information is provided by music rather than images.
Temporally Guided Music-to-Body-Movement Generation
This paper presents a neural network model to generate virtual violinist's 3-D skeleton movements from music audio.
A Human-Computer Duet System for Music Performance
Virtual musicians have become a remarkable phenomenon in the contemporary multimedia arts.
Knowledge-guided Pairwise Reconstruction Network for Weakly Supervised Referring Expression Grounding
Weakly supervised referring expression grounding (REG) aims at localizing the referential entity in an image according to linguistic query, where the mapping between the image region (proposal) and the query is unknown in the training stage.
Cascaded Partial Decoder for Fast and Accurate Salient Object Detection
In this paper, we propose a novel Cascaded Partial Decoder (CPD) framework for fast and accurate salient object detection.
Ranked #1 on
RGB Salient Object Detection
on ISTD
Multi-layered Cepstrum for Instantaneous Frequency Estimation
We propose the multi-layered cepstrum (MLC) method to estimate multiple fundamental frequencies (MF0) of a signal under challenging contamination such as high-pass filter noise.
A Streamlined Encoder/Decoder Architecture for Melody Extraction
Our experiments on both vocal melody extraction and general melody extraction validate the effectiveness of the proposed model.
Vocal melody extraction using patch-based CNN
A patch-based convolutional neural network (CNN) model presented in this paper for vocal melody extraction in polyphonic music is inspired from object detection in image processing.
Sound Audio and Speech Processing
Between Homomorphic Signal Processing and Deep Neural Networks: Constructing Deep Algorithms for Polyphonic Music Transcription
This paper presents a new approach in understanding how deep neural networks (DNNs) work by applying homomorphic signal processing techniques.
