research
∙
07/07/2023
Training Ensembles with Inliers and Outliers for Semi-supervised Active Learning
Deep active learning in the presence of outlier examples poses a realist...
share
research
∙
06/15/2023
The 2023 Video Similarity Dataset and Challenge
This work introduces a dataset, benchmark, and challenge for the problem...
research
∙
05/05/2023
HSCNet++: Hierarchical Scene Coordinate Classification and Regression for Visual Localization with Transformer
Visual localization is critical to many applications in computer vision ...
research
∙
04/06/2023
Self-Supervised Video Similarity Learning
We introduce S^2VS, a video similarity learning approach with self-super...
research
∙
03/28/2023
Rethinking matching-based few-shot action recognition
Few-shot action recognition, i.e. recognizing new action classes given o...
research
∙
10/11/2022
Large-to-small Image Resolution Asymmetry in Deep Metric Learning
Deep metric learning for vision is trained by optimizing a representatio...
research
∙
02/26/2022
Edge Augmentation for Large-Scale Sketch Recognition without Sketches
This work addresses scaling up the sketch classification task into a lar...
research
∙
02/08/2022
Results and findings of the 2021 Image Similarity Challenge
The 2021 Image Similarity Challenge introduced a dataset to serve as a n...
research
∙
02/03/2022
The Met Dataset: Instance-level Recognition for Artworks
This work introduces a dataset for large-scale instance-level recognitio...
research
∙
06/17/2021
The 2021 Image Similarity Dataset and Challenge
This paper introduces a new benchmark for large-scale image similarity d...
research
∙
07/26/2020
Learning and aggregating deep local descriptors for instance-level recognition
We propose an efficient method to learn deep local descriptors for insta...
research
∙
10/01/2019
Graph convolutional networks for learning with few clean and many noisy labels
In this work we consider the problem of learning a classifier from noisy...
research
∙
08/24/2019
Targeted Mismatch Adversarial Attack: Query with a Flower to Retrieve the Tower
Access to online visual search engines implies sharing of private user c...
research
∙
04/15/2019
Explicit Spatial Encoding for Deep Local Descriptors
We propose a kernelized deep local-patch descriptor based on efficient m...
research
∙
04/09/2019
Label Propagation for Deep Semi-supervised Learning
Semi-supervised learning is becoming increasingly important because it c...
research
∙
11/27/2018
Understanding and Improving Kernel Local Descriptors
We propose a multiple-kernel local-patch descriptor based on efficient m...
research
∙
07/23/2018
Hybrid Diffusion: Spectral-Temporal Graph Filtering for Manifold Ranking
State of the art image retrieval performance is achieved with CNN featur...
research
∙
03/29/2018
Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking
In this paper we address issues with image retrieval benchmarking on sta...
research
∙
03/29/2018
Mining on Manifolds: Metric Learning without Labels
In this work we present a novel unsupervised framework for hard training...
research
∙
11/03/2017
Fine-tuning CNN Image Retrieval with No Human Annotation
Image descriptors based on activations of Convolutional Neural Networks ...
research
∙
09/14/2017
Unsupervised deep object discovery for instance recognition
Severe background clutter is challenging in many computer vision tasks, ...
research
∙
09/11/2017
Generic Sketch-Based Retrieval Learned without Drawing a Single Sketch
We cast the sketch-based retrieval as edge-map matching. A shared convol...
research
∙
07/25/2017
Multiple-Kernel Local-Patch Descriptor
We propose a multiple-kernel local-patch descriptor based on efficient m...
research
∙
03/20/2017
Fast Spectral Ranking for Similarity Search
Despite the success of deep learning on representing images for particul...
research
∙
11/16/2016
Efficient Diffusion on Region Manifolds: Recovering Small Objects with Compact CNN Representations
Query expansion is a popular method to improve the quality of image retr...
research
∙
04/08/2016
CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples
Convolutional Neural Networks (CNNs) achieve state-of-the-art performanc...
research
∙
10/29/2014
A comparison of dense region detectors for image search and fine-grained classification
We consider a pipeline for image classification or search based on codin...
research
∙
07/08/2014