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 …

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 …

Video inpainting, which aims at filling in missing regions in a video, remains challenging due
to the difficulty of preserving the precise spatial and temporal coherence of video contents. In …

We introduce a new task--language-driven video inpainting which uses natural language
instructions to guide the inpainting process. This approach overcomes the limitations of …

Video tampering methods have witnessed considerable progress in recent years. This is
partly due to the rapid development of advanced deep learning methods, and also due to …

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 …

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 …

We propose a novel video inpainting algorithm that simultaneously hallucinates missing
appearance and motion (optical flow) information, building upon the recent'Deep Image …

In recent years, video surveillance has become essential for security applications used to
monitor many organizations and locations, and it is therefore important to ensure the …