1 code implementation • 13 Mar 2024 • Tiange Xiang, Yixiao Zhang, Yongyi Lu, Alan Yuille, Chaoyi Zhang, Weidong Cai, Zongwei Zhou
To this end, we propose a Simple Space-Aware Memory Matrix for In-painting and Detecting anomalies from radiography images (abbreviated as SimSID).
1 code implementation • 14 Feb 2024 • Liwei Lin, Gus Xia, Yixiao Zhang, Junyan Jiang
We apply this method to fine-tune MusicGen, a leading autoregressive music generation model.
no code implementations • 9 Feb 2024 • Yixiao Zhang, Yukara Ikemiya, Gus Xia, Naoki Murata, Marco Martínez, Wei-Hsiang Liao, Yuki Mitsufuji, Simon Dixon
This paper introduces a novel approach to the editing of music generated by such models, enabling the modification of specific attributes, such as genre, mood and instrument, while maintaining other aspects unchanged.
1 code implementation • 16 Nov 2023 • Ilaria Manco, Benno Weck, Seungheon Doh, Minz Won, Yixiao Zhang, Dmitry Bogdanov, Yusong Wu, Ke Chen, Philip Tovstogan, Emmanouil Benetos, Elio Quinton, György Fazekas, Juhan Nam
We introduce the Song Describer dataset (SDD), a new crowdsourced corpus of high-quality audio-caption pairs, designed for the evaluation of music-and-language models.
1 code implementation • 26 Oct 2023 • Liwei Lin, Gus Xia, Junyan Jiang, Yixiao Zhang
We aim to further equip the models with direct and content-based controls on innate music languages such as pitch, chords and drum track.
no code implementations • 19 Oct 2023 • Yixiao Zhang, Akira Maezawa, Gus Xia, Kazuhiko Yamamoto, Simon Dixon
Creating music is iterative, requiring varied methods at each stage.
no code implementations • 20 Sep 2023 • Giovanni Bindi, Nils Demerlé, Rodrigo Diaz, David Genova, Aliénor Golvet, Ben Hayes, Jiawen Huang, Lele Liu, Vincent Martos, Sarah Nabi, Teresa Pelinski, Lenny Renault, Saurjya Sarkar, Pedro Sarmento, Cyrus Vahidi, Lewis Wolstanholme, Yixiao Zhang, Axel Roebel, Nick Bryan-Kinns, Jean-Louis Giavitto, Mathieu Barthet
The students represent the future generation of AI and music researchers.
1 code implementation • 10 Aug 2023 • Nick Bryan-Kinns, Berker Banar, Corey Ford, Courtney N. Reed, Yixiao Zhang, Simon Colton, Jack Armitage
We increase the explainability of the model by: i) using latent space regularisation to force some specific dimensions of the latent space to map to meaningful musical attributes, ii) providing a user interface feedback loop to allow people to adjust dimensions of the latent space and observe the results of these changes in real-time, iii) providing a visualisation of the musical attributes in the latent space to help people understand and predict the effect of changes to latent space dimensions.
1 code implementation • 1 Jun 2023 • Yixiao Zhang, Xinyi Li, Huimiao Chen, Alan Yuille, Yaoyao Liu, Zongwei Zhou
The ability to dynamically extend a model to new data and classes is critical for multiple organ and tumor segmentation.
2 code implementations • ICCV 2023 • Jie Liu, Yixiao Zhang, Jie-Neng Chen, Junfei Xiao, Yongyi Lu, Bennett A. Landman, Yixuan Yuan, Alan Yuille, Yucheng Tang, Zongwei Zhou
The proposed model is developed from an assembly of 14 datasets, using a total of 3, 410 CT scans for training and then evaluated on 6, 162 external CT scans from 3 additional datasets.
Ranked #1 on Organ Segmentation on BTCV
1 code implementation • 10 Nov 2022 • Runbang Zhang, Yixiao Zhang, Kai Shao, Ying Shan, Gus Xia
In this study, we explore the representation mapping from the domain of visual arts to the domain of music, with which we can use visual arts as an effective handle to control music generation.
1 code implementation • 21 Sep 2022 • Junyan Jiang, Daniel Chin, Yixiao Zhang, Gus Xia
In this paper, we explore a data-driven approach to automatically extract hierarchical metrical structures from scores.
1 code implementation • 24 Aug 2022 • Yixiao Zhang, Junyan Jiang, Gus Xia, Simon Dixon
Lyric interpretations can help people understand songs and their lyrics quickly, and can also make it easier to manage, retrieve and discover songs efficiently from the growing mass of music archives.
1 code implementation • ICLR 2022 • Jieru Mei, Yucheng Han, Yutong Bai, Yixiao Zhang, Yingwei Li, Xianhang Li, Alan Yuille, Cihang Xie
Specifically, our modifications in Fast AdvProp are guided by the hypothesis that disentangled learning with adversarial examples is the key for performance improvements, while other training recipes (e. g., paired clean and adversarial training samples, multi-step adversarial attackers) could be largely simplified.
2 code implementations • CVPR 2023 • Tiange Xiang, Yixiao Zhang, Yongyi Lu, Alan L. Yuille, Chaoyi Zhang, Weidong Cai, Zongwei Zhou
Radiography imaging protocols focus on particular body regions, therefore producing images of great similarity and yielding recurrent anatomical structures across patients.
no code implementations • 26 Oct 2021 • Yixiao Zhang, Adam Kortylewski, Qing Liu, Seyoun Park, Benjamin Green, Elizabeth Engle, Guillermo Almodovar, Ryan Walk, Sigfredo Soto-Diaz, Janis Taube, Alex Szalay, Alan Yuille
It only requires annotations on isolated nucleus, rather than on all nuclei in the dataset.
1 code implementation • ICCV 2021 • Zhuowan Li, Elias Stengel-Eskin, Yixiao Zhang, Cihang Xie, Quan Tran, Benjamin Van Durme, Alan Yuille
Our experiments show CCO substantially boosts the performance of neural symbolic methods on real images.
2 code implementations • 17 Aug 2020 • Ziyu Wang, Dingsu Wang, Yixiao Zhang, Gus Xia
While deep generative models have become the leading methods for algorithmic composition, it remains a challenging problem to control the generation process because the latent variables of most deep-learning models lack good interpretability.
2 code implementations • 17 Aug 2020 • Ziyu Wang, Yiyi Zhang, Yixiao Zhang, Junyan Jiang, Ruihan Yang, Junbo Zhao, Gus Xia
The dominant approach for music representation learning involves the deep unsupervised model family variational autoencoder (VAE).
no code implementations • 19 Feb 2020 • Yixiao Zhang, Xiaosong Wang, Ziyue Xu, Qihang Yu, Alan Yuille, Daguang Xu
In addition, we proposed a new evaluation metric for radiology image reporting with the assistance of the same composed graph.
no code implementations • CVPR 2020 • Qihang Yu, Dong Yang, Holger Roth, Yutong Bai, Yixiao Zhang, Alan L. Yuille, Daguang Xu
3D convolution neural networks (CNN) have been proved very successful in parsing organs or tumours in 3D medical images, but it remains sophisticated and time-consuming to choose or design proper 3D networks given different task contexts.