8 citations · 10 across the 8 of their papers we have counts for
6 papers · 1 filter
Reimagine Video Dynamics
Yu Yuan, Yawen Lu, Guoxian Song +5
Most video editing methods focus on changing the appearance of the source video, while offering limited control over its dynamics. We introduce Reimagine Video Dynamics (RVD), a fr…
ProMotion: Prototypes As Motion Learners
Yawen Lu, Dongfang Liu, Qifan Wang +6
In this work, we introduce ProMotion, a unified prototypical framework engineered to model fundamental motion tasks. ProMotion offers a range of compelling attributes that set it a…
Prototypical Transformer as Unified Motion Learners
Cheng Han, Yawen Lu, Guohao Sun +9
In this work, we introduce the Prototypical Transformer (ProtoFormer), a general and unified framework that approaches various motion tasks from a prototype perspective. ProtoForme…
Diffusion Attack: Leveraging Stable Diffusion for Naturalistic Image Attacking
Qianyu Guo, Jiaming Fu, Yawen Lu +1
In Virtual Reality (VR), adversarial attack remains a significant security threat. Most deep learning-based methods for physical and digital adversarial attacks focus on enhancing…
DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-based 3D Vision
Lu Ling, Yichen Sheng, Zhi Tu +17
We have witnessed significant progress in deep learning-based 3D vision, ranging from neural radiance field (NeRF) based 3D representation learning to applications in novel view sy…
TransFlow: Transformer as Flow Learner
Yawen Lu, Qifan Wang, Siqi Ma +4
Optical flow is an indispensable building block for various important computer vision tasks, including motion estimation, object tracking, and disparity measurement. In this work,…