Location-Free Camouflage Generation Network
Yangyang Li, Wei Zhai, Yang Cao, Zheng-jun Zha

TL;DR
This paper introduces LCG-Net, a fast and effective location-free camouflage generation network that fuses high-level features of foreground and background to produce natural-looking camouflage images, especially in complex multi-appearance regions.
Contribution
The paper proposes a novel LCG-Net with a Position-aligned Structure Fusion module and new loss functions, enabling efficient and high-quality camouflage generation in arbitrary structures and multi-appearance regions.
Findings
Outperforms state-of-the-art in multi-appearance regions
Much faster than previous methods
Produces natural and continuous camouflage images
Abstract
Camouflage is a common visual phenomenon, which refers to hiding the foreground objects into the background images, making them briefly invisible to the human eye. Previous work has typically been implemented by an iterative optimization process. However, these methods struggle in 1) efficiently generating camouflage images using foreground and background with arbitrary structure; 2) camouflaging foreground objects to regions with multiple appearances (e.g. the junction of the vegetation and the mountains), which limit their practical application. To address these problems, this paper proposes a novel Location-free Camouflage Generation Network (LCG-Net) that fuse high-level features of foreground and background image, and generate result by one inference. Specifically, a Position-aligned Structure Fusion (PSF) module is devised to guide structure feature fusion based on the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsVisual Attention and Saliency Detection · Image Enhancement Techniques · Advanced Image and Video Retrieval Techniques
