27 citations · 81 across the 11 of their papers we have counts for
11 papers
Dior-CVAE: Pre-trained Language Models and Diffusion Priors for Variational Dialog Generation
Tianyu Yang, Thy Thy Tran, Iryna Gurevych
Current variational dialog models have employed pre-trained language models (PLMs) to parameterize the likelihood and posterior distributions. However, the Gaussian assumption made…
HOSNeRF: Dynamic Human-Object-Scene Neural Radiance Fields from a Single Video
Jia-Wei Liu, Yan-Pei Cao, Tianyuan Yang +5
We introduce HOSNeRF, a novel 360° free-viewpoint rendering method that reconstructs neural radiance fields for dynamic human-object-scene from a single monocular in-the-wild video…
SimVTP: Simple Video Text Pre-training with Masked Autoencoders
Yue Ma, Tianyu Yang, Yin Shan +1
This paper presents SimVTP: a Simple Video-Text Pretraining framework via masked autoencoders. We randomly mask out the spatial-temporal tubes of input video and the word tokens of…
Latent Video Diffusion Models for High-Fidelity Long Video Generation
Yingqing He, Tianyu Yang, Yong Zhang +2
AI-generated content has attracted lots of attention recently, but photo-realistic video synthesis is still challenging. Although many attempts using GANs and autoregressive models…
SWEM: Towards Real-Time Video Object Segmentation with Sequential Weighted Expectation-Maximization
Zhihui Lin, Tianyu Yang, Maomao Li +4
Matching-based methods, especially those based on space-time memory, are significantly ahead of other solutions in semi-supervised video object segmentation (VOS). However, continu…
LocVTP: Video-Text Pre-training for Temporal Localization
Meng Cao, Tianyu Yang, Junwu Weng +3
Video-Text Pre-training (VTP) aims to learn transferable representations for various downstream tasks from large-scale web videos. To date, almost all existing VTP methods are limi…
Unsupervised Pre-training for Temporal Action Localization Tasks
Can Zhang, Tianyu Yang, Junwu Weng +3
Unsupervised video representation learning has made remarkable achievements in recent years. However, most existing methods are designed and optimized for video classification. The…
Semantic-Preserving Linguistic Steganography by Pivot Translation and Semantic-Aware Bins Coding
Tianyu Yang, Hanzhou Wu, Biao Yi +2
Linguistic steganography (LS) aims to embed secret information into a highly encoded text for covert communication. It can be roughly divided to two main categories, i.e., modifica…
Motion-aware Contrastive Video Representation Learning via Foreground-background Merging
Shuangrui Ding, Maomao Li, Tianyu Yang +5
In light of the success of contrastive learning in the image domain, current self-supervised video representation learning methods usually employ contrastive loss to facilitate vid…
VideoMoCo: Contrastive Video Representation Learning with Temporally Adversarial Examples
Tian Pan, Yibing Song, Tianyu Yang +2
MoCo is effective for unsupervised image representation learning. In this paper, we propose VideoMoCo for unsupervised video representation learning. Given a video sequence as an i…
Generative adversarial network based on chaotic time series
Makoto Naruse, Takashi Matsubara, Nicolas Chauvet +3
Generative adversarial network (GAN) is gaining increased importance in artificially constructing natural images and related functionalities wherein two networks called generator a…