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Found 6 papers, 3 papers with code
Magicremover: Tuning-free Text-guided Image inpainting with Diffusion Models
In this paper, we propose MagicRemover, a tuning-free method that leverages the powerful diffusion models for text-guided image inpainting.
Exploiting Optical Flow Guidance for Transformer-Based Video Inpainting
Transformers have been widely used for video processing owing to the multi-head self attention (MHSA) mechanism.
Ranked #1 on
Video Inpainting
on DAVIS
(SSIM (square) metric)
Template-guided Hierarchical Feature Restoration for Anomaly Detection
Targeting for detecting anomalies of various sizes for complicated normal patterns, we propose a Template-guided Hierarchical Feature Restoration method, which introduces two key techniques, bottleneck compression and template-guided compensation, for anomaly-free feature restoration.
Ranked #11 on
Anomaly Detection
on MVTec LOCO AD
Flow-Guided Transformer for Video Inpainting
Especially in spatial transformer, we design a dual perspective spatial MHSA, which integrates the global tokens to the window-based attention.
Inertia-Guided Flow Completion and Style Fusion for Video Inpainting
We propose a flow completion network to align and aggregate flow features from the consecutive flow sequences based on the inertia prior.
Feature Selective Networks for Object Detection
The RoI-based sub-region attention map and aspect ratio attention map are selectively pooled from the banks, and then used to refine the original RoI features for RoI classification.
