Flow-based propagation and spatiotemporal Transformer are two mainstream mechanisms
in video inpainting (VI). Despite the effectiveness of these components, they still suffer from …

Optical flow, which captures motion information across frames, is exploited in recent video
inpainting methods through propagating pixels along its trajectories. However, the hand …

Video anomaly detection (VAD) is a significant computer vision problem. Existing deep
neural network (DNN) based VAD methods mostly follow the route of frame reconstruction or …

We propose a flow-guided transformer, which innovatively leverage the motion discrepancy
exposed by optical flows to instruct the attention retrieval in transformer for high fidelity video …

Physical objects have inertia, which resists changes in the velocity and motion direction.
Inspired by this, we introduce inertia prior that optical flow, which reflects object motion in a …

While language-guided image manipulation has made remarkable progress, the challenge
of how to instruct the manipulation process faithfully reflecting human intentions persists. An …

Video inpainting remains a challenging problem to fill with plausible and coherent content in
unknown areas in video frames despite the prevalence of data-driven methods. Although …

Video inpainting aims at filling in missing regions of a video. However, when dealing with
dynamic scenes with camera or object movements, annotating the inpainting target …

Abstract Video-to-Video synthesis (Vid2Vid) has achieved remarkable results in generating
a photo-realistic video from a sequence of semantic maps. However, this pipeline suffers …

As a promising vehicular communication technology, Cellular Vehicle-to-Everything (C-V2X)
is expected to ensure the safety and convenience of Intelligent Transportation Systems (ITS) …