2 citations · 3 across the 4 of their papers we have counts for
9 papers
Complete Cross-triplet Loss in Label Space for Audio-visual Cross-modal Retrieval
Donghuo Zeng, Yanan Wang, Jianming Wu +1
The heterogeneity gap problem is the main challenge in cross-modal retrieval. Because cross-modal data (e.g. audiovisual) have different distributions and representations that cann…
Learning Explicit and Implicit Latent Common Spaces for Audio-Visual Cross-Modal Retrieval
Donghuo Zeng, Jianming Wu, Gen Hattori +2
Learning common subspace is prevalent way in cross-modal retrieval to solve the problem of data from different modalities having inconsistent distributions and representations that…
SHECS: A Local Smart Hands-free Elderly Care Support System on Smart AR Glasses with AI Technology
Donghuo Zeng, Jianming Wu, Bo Yang +6
Some elderly care homes attempt to remedy the shortage of skilled caregivers and provide long-term care for the elderly residents, by enhancing the management of the care support s…
MusicTM-Dataset for Joint Representation Learning among Sheet Music, Lyrics, and Musical Audio
Donghuo Zeng, Yi Yu, Keizo Oyama
This work present a music dataset named MusicTM-Dataset, which is utilized in improving the representation learning ability of different types of cross-modal retrieval (CMR). Littl…
Unsupervised Generative Adversarial Alignment Representation for Sheet music, Audio and Lyrics
Donghuo Zeng, Yi Yu, Keizo Oyama
Sheet music, audio, and lyrics are three main modalities during writing a song. In this paper, we propose an unsupervised generative adversarial alignment representation (UGAAR) mo…
Learning Joint Embedding for Cross-Modal Retrieval
Donghuo Zeng
A cross-modal retrieval process is to use a query in one modality to obtain relevant data in another modality. The challenging issue of cross-modal retrieval lies in bridging the h…