1 code implementation • 29 Oct 2023 • Yao Yao, Peike Li, BoYu Chen, Alex Wang
With rapid advances in generative artificial intelligence, the text-to-music synthesis task has emerged as a promising direction for music generation from scratch.
no code implementations • 20 Aug 2023 • Chen Liu, Peike Li, Hu Zhang, Lincheng Li, Zi Huang, Dadong Wang, Xin Yu
In a nutshell, our BAVS is designed to eliminate the interference of background noise or off-screen sounds in segmentation by establishing the audio-visual correspondences in an explicit manner.
2 code implementations • 9 Aug 2023 • Peike Li, BoYu Chen, Yao Yao, Yikai Wang, Allen Wang, Alex Wang
Despite the task's significance, prevailing generative models exhibit limitations in music quality, computational efficiency, and generalization.
Ranked #1 on Text-to-Music Generation on MusicCaps
no code implementations • 31 Jul 2023 • Chen Liu, Peike Li, Xingqun Qi, Hu Zhang, Lincheng Li, Dadong Wang, Xin Yu
However, we observed that prior arts are prone to segment a certain salient object in a video regardless of the audio information.
no code implementations • 12 Jul 2022 • Xiao Pan, Hao Luo, Weihua Chen, Fan Wang, Hao Li, Wei Jiang, Jianming Zhang, Jianyang Gu, Peike Li
To address this issue, we propose the Ranking-based Backward Compatible Learning (RBCL), which directly optimizes the ranking metric between new features and old features.
no code implementations • 24 May 2022 • Zhikang Li, Huiling Zhou, Shuai Bai, Peike Li, Chang Zhou, Hongxia Yang
The fashion industry has diverse applications in multi-modal image generation and editing.
1 code implementation • 29 Mar 2022 • Xiao Pan, Peike Li, Zongxin Yang, Huiling Zhou, Chang Zhou, Hongxia Yang, Jingren Zhou, Yi Yang
By contrast, pixel-level optimization is more explicit, however, it is sensitive to the visual quality of training data and is not robust to object deformation.
no code implementations • ICCV 2021 • Peike Li, Xin Yu, Yi Yang
By iteratively updating the latent representations and our decoder, our DAP-FSR will be adapted to the target domain, thus achieving authentic and high-quality upsampled HR faces.
no code implementations • NeurIPS 2020 • Peike Li, Yunchao Wei, Yi Yang
Concretely, by exploring the pair-wise and list-wise structures, we impose the relations of generated visual features to be consistent with their counterparts in the semantic word embedding space.
2 code implementations • 22 Oct 2019 • Peike Li, Yunqiu Xu, Yunchao Wei, Yi Yang
To tackle the problem of learning with label noises, this work introduces a purification strategy, called Self-Correction for Human Parsing (SCHP), to progressively promote the reliability of the supervised labels as well as the learned models.
Ranked #2 on Human Part Segmentation on PASCAL-Part