42 citations · 61 across the 6 of their papers we have counts for
6 papers
Through the PRISM: Preference Representation in Intermediate States of Video Diffusion Models
Haoxuan Wu, Lai Man Po, Mengyang Liu +3
Video reward models are central to aligning video diffusion models with human preferences, yet existing ones are external vision-language models that score clean, decoded pixels. S…
PTVD: A Large-Scale Plot-Oriented Multimodal Dataset Based on Television Dramas
Chen Li, Xutan Peng, Teng Wang +5
Art forms such as movies and television (TV) dramas are reflections of the real world, which have attracted much attention from the multimodal learning community recently. However,…
SVCNet: Scribble-based Video Colorization Network with Temporal Aggregation
Yuzhi Zhao, Lai-Man Po, Kangcheng Liu +5
In this paper, we propose a scribble-based video colorization network with temporal aggregation called SVCNet. It can colorize monochrome videos based on different user-given color…
Deep Image Style Transfer from Freeform Text
Tejas Santanam, Mengyang Liu, Jiangyue Yu +1
This paper creates a novel method of deep neural style transfer by generating style images from freeform user text input. The language model and style transfer model form a seamles…
Contrastive Spatio-Temporal Pretext Learning for Self-supervised Video Representation
Yujia Zhang, Lai-Man Po, Xuyuan Xu +5
Spatio-temporal representation learning is critical for video self-supervised representation. Recent approaches mainly use contrastive learning and pretext tasks. However, these ap…
VCGAN: Video Colorization with Hybrid Generative Adversarial Network
Yuzhi Zhao, Lai-Man Po, Wing-Yin Yu +4
We propose a hybrid recurrent Video Colorization with Hybrid Generative Adversarial Network (VCGAN), an improved approach to video colorization using end-to-end learning. The VCGAN…