85 citations · 267 across the 19 of their papers we have counts for
9 papers · 1 filter
LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models
Yaohui Wang, Xinyuan Chen, Xin Ma +17
This work aims to learn a high-quality text-to-video (T2V) generative model by leveraging a pre-trained text-to-image (T2I) model as a basis. It is a highly desirable yet challengi…
LAC: Latent Action Composition for Skeleton-based Action Segmentation
Di Yang, Yaohui Wang, Antitza Dantcheva +4
Skeleton-based action segmentation requires recognizing composable actions in untrimmed videos. Current approaches decouple this problem by first extracting local visual features f…
InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation
Yi Wang, Yinan He, Yizhuo Li +13
This paper introduces InternVid, a large-scale video-centric multimodal dataset that enables learning powerful and transferable video-text representations for multimodal understand…
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
Yuwei Guo, Ceyuan Yang, Anyi Rao +6
With the advance of text-to-image (T2I) diffusion models (e.g., Stable Diffusion) and corresponding personalization techniques such as DreamBooth and LoRA, everyone can manifest th…
Long-Term Rhythmic Video Soundtracker
Jiashuo Yu, Yaohui Wang, Xinyuan Chen +2
We consider the problem of generating musical soundtracks in sync with rhythmic visual cues. Most existing works rely on pre-defined music representations, leading to the incompete…
Self-Supervised Video Representation Learning via Latent Time Navigation
Di Yang, Yaohui Wang, Quan Kong +4
Self-supervised video representation learning aimed at maximizing similarity between different temporal segments of one video, in order to enforce feature persistence over time. Th…
LEO: Generative Latent Image Animator for Human Video Synthesis
Yaohui Wang, Xin Ma, Xinyuan Chen +4
Spatio-temporal coherency is a major challenge in synthesizing high quality videos, particularly in synthesizing human videos that contain rich global and local deformations. To re…
Hierarchical Diffusion Autoencoders and Disentangled Image Manipulation
Zeyu Lu, Chengyue Wu, Xinyuan Chen +4
Diffusion models have attained impressive visual quality for image synthesis. However, how to interpret and manipulate the latent space of diffusion models has not been extensively…
Learning Invariance from Generated Variance for Unsupervised Person Re-identification
Hao Chen, Yaohui Wang, Benoit Lagadec +2
This work focuses on unsupervised representation learning in person re-identification (ReID). Recent self-supervised contrastive learning methods learn invariance by maximizing the…