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Found 13 papers, 5 papers with code
Task-conditioned Domain Adaptation for Pedestrian Detection in Thermal Imagery
Despite its broad application and interest, it remains a challenging problem in part due to the vast range of conditions under which it must be robust.
Error assessment of microwave holography inversion for shallow buried objects
Holographic imaging is a technique that uses microwave energy to create a three-dimensional image of an object or scene.
Zero-Shot Composed Image Retrieval with Textual Inversion
Composed Image Retrieval (CIR) aims to retrieve a target image based on a query composed of a reference image and a relative caption that describes the difference between the two images.
Conditioned and Composed Image Retrieval Combining and Partially Fine-Tuning CLIP-Based Features
The proposed method is based on an initial training stage where a simple combination of visual and textual features is used, to fine-tune the CLIP text encoder.
Ranked #2 on
Image Retrieval
on Fashion IQ
Effective Conditioned and Composed Image Retrieval Combining CLIP-Based Features
the visual content of the query image.
Ranked #4 on
Image Retrieval
on CIRR
Partially fake it till you make it: mixing real and fake thermal images for improved object detection
In this paper we propose a novel data augmentation approach for visual content domains that have scarce training datasets, compositing synthetic 3D objects within real scenes.
Robust pedestrian detection in thermal imagery using synthesized images
Experimental results demonstrate the effectiveness of our approach: using less than 50\% of available real thermal training data, and relying on synthesized data generated by our model in the domain adaptation phase, our detector achieves state-of-the-art results on the KAIST Multispectral Pedestrian Detection Benchmark; even if more real thermal data is available adding GAN generated images to the training data results in improved performance, thus showing that these images act as an effective form of data augmentation.
Inner Eye Canthus Localization for Human Body Temperature Screening
As additional contribution, we enrich the original dataset by using the annotated landmarks to deform and project the 3DMM onto the images.
Image Retrieval using Multi-scale CNN Features Pooling
In this paper, we address the problem of image retrieval by learning images representation based on the activations of a Convolutional Neural Network.
Deep Generative Adversarial Compression Artifact Removal
Moreover we show that our approach can be used as a pre-processing step for object detection in case images are degraded by compression to a point that state-of-the art detectors fail.
Compact Hash Codes for Efficient Visual Descriptors Retrieval in Large Scale Databases
In this paper we present an efficient method for visual descriptors retrieval based on compact hash codes computed using a multiple k-means assignment.
Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement and Retrieval
Where previous reviews on content-based image retrieval emphasize on what can be seen in an image to bridge the semantic gap, this survey considers what people tag about an image.
A Data-Driven Approach for Tag Refinement and Localization in Web Videos
Our approach exploits collective knowledge embedded in user-generated tags and web sources, and visual similarity of keyframes and images uploaded to social sites like YouTube and Flickr, as well as web sources like Google and Bing.
