Search Results for author:
Found 7 papers, 1 papers with code
Towards Total Recall in Industrial Anomaly Detection
Being able to spot defective parts is a critical component in large-scale industrial manufacturing.
Ranked #3 on
Anomaly Detection
on AeBAD-V
Learning a Complete Image Indexing Pipeline
To work at scale, a complete image indexing system comprises two components: An inverted file index to restrict the actual search to only a subset that should contain most of the items relevant to the query; An approximate distance computation mechanism to rapidly scan these lists.
SUBIC: A supervised, structured binary code for image search
For large-scale visual search, highly compressed yet meaningful representations of images are essential.
Kernel Square-Loss Exemplar Machines for Image Retrieval
Zepeda and Perez have recently demonstrated the promise of the exemplar SVM (ESVM) as a feature encoder for image retrieval.
Approximate search with quantized sparse representations
This paper tackles the task of storing a large collection of vectors, such as visual descriptors, and of searching in it.
Exemplar SVMs as Visual Feature Encoders
In this work, we investigate the use of exemplar SVMs (linear SVMs trained with one positive example only and a vast collection of negative examples) as encoders that turn generic image features into new, task-tailored features.
Hybrid multi-layer Deep CNN/Aggregator feature for image classification
A second variant of our approach that includes the fully connected DCNN layers significantly outperforms Fisher vector schemes and performs comparably to DCNN approaches adapted to Pascal VOC 2007, yet at only a small fraction of the training and testing cost.
