Landmark Recognition
13 papers with code • 2 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Landmark Recognition
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Datasets
Google Landmarks Dataset v2
Chest x-ray landmark dataset
Latest papers
A Study on Self-Supervised Pretraining for Vision Problems in Gastrointestinal Endoscopy
esandml/ssl4gie
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In this work, we study the fine-tuned performance of models with ResNet50 and ViT-B backbones pretrained in self-supervised and supervised manners with ImageNet-1k and Hyperkvasir-unlabelled (self-supervised only) in a range of GIE vision tasks.
Efficient large-scale image retrieval with deep feature orthogonality and Hybrid-Swin-Transformers
christofhenkel/kaggle-landmark-2021-1st-place
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We present an efficient end-to-end pipeline for largescale landmark recognition and retrieval.
Clusformer: A Transformer Based Clustering Approach to Unsupervised Large-Scale Face and Visual Landmark Recognition
uark-cviu/Intraformer
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CVPR 2021
This work therefore presents the Clusformer, a simple but new perspective of Transformer based approach, to automatic visual clustering via its unsupervised attention mechanism.
Google Landmark Recognition 2020 Competition Third Place Solution
haqishen/Google-Landmark-Recognition-2020-3rd-Place-Solution
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We present our third place solution to the Google Landmark Recognition 2020 competition.
Supporting large-scale image recognition with out-of-domain samples
psinger/kaggle-landmark-recognition-2020-1st-place
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This article presents an efficient end-to-end method to perform instance-level recognition employed to the task of labeling and ranking landmark images.
Google Landmarks Dataset v2 -- A Large-Scale Benchmark for Instance-Level Recognition and Retrieval
GLDv2 is the largest such dataset to date by a large margin, including over 5M images and 200k distinct instance labels.
Two-stage Discriminative Re-ranking for Large-scale Landmark Retrieval
cvdfoundation/google-landmark
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Due to the variance of the images, which include extreme viewpoint changes such as having to retrieve images of the exterior of a landmark from images of the interior, this is very challenging for approaches based exclusively on visual similarity.
2nd Place and 2nd Place Solution to Kaggle Landmark Recognition andRetrieval Competition 2019
We present a retrieval based system for landmark retrieval and recognition challenge. There are five parts in retrieval competition system, including feature extraction and matching to get candidates queue; database augmentation and query extension searching; reranking from recognition results and local feature matching.
Large-scale Landmark Retrieval/Recognition under a Noisy and Diverse Dataset
lyakaap/Landmark2019-1st-and-3rd-Place-Solution
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Besides, we devise a discriminative re-ranking method to address the diversity of the dataset for landmark retrieval.
Improving Landmark Recognition using Saliency detection and Feature classification
AKASH2907/indian_landmark_recognition
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Image Landmark Recognition has been one of the most sought-after classification challenges in the field of vision and perception.
