paper-with-me

Papers

Location Sensitive Image Retrieval and Tagging

2020-07-07 · ECCV 2020 8 · Raul Gomez, Jaume Gibert, Lluis Gomez, Dimosthenis Karatzas

People from different parts of the globe describe objects and concepts in distinct manners. Visual appearance can thus vary across different geographic locations, which makes location a relevant contextual information when analysing visual data. In this work, we address the task of image retrieval related to a given tag conditioned on a certain location on Earth. We present LocSens, a model that learns to rank triplets of images, tags and coordinates by plausibility, and two training strategies to balance the location influence in the final ranking. LocSens learns to fuse textual and location information of multimodal queries to retrieve related images at different levels of location granularity, and successfully utilizes location information to improve image tagging.

📄 PDF Abstract BibTeX arXiv:2007.03375

Code (0)

등록된 구현이 없습니다.

Tasks

Image RetrievalRetrievalTAG

Similar Papers 제목 키워드 기반

Context Aware Object Geotagging

2021-08-13 · Chao-Jung Liu, Matej Ulicny, Michael Manzke, Rozenn Dahyot

Localization of street objects from images has gained a lot of attention in recent years. We propose an approach to improve asset geolocation from street view imagery by enhancing the quality of the metadata associated w…

Object

Deep Learning Classification With Noisy Labels

2020-04-23 · Guillaume Sanchez, Vincente Guis, Ricard Marxer, Frédéric Bouchara

Deep Learning systems have shown tremendous accuracy in image classification, at the cost of big image datasets. Collecting such amounts of data can lead to labelling errors in the training set. Indexing multimedia conte…

ClassificationDeep LearningFace RecognitionGeneral Classification+3

Sampled Image Tagging and Retrieval Methods on User Generated Content

2016-11-21 · Karl Ni, Kyle Zaragoza, Charles Foster, Carmen Carrano 외

Traditional image tagging and retrieval algorithms have limited value as a result of being trained with heavily curated datasets. These limitations are most evident when arbitrary search words are used that do not inters…

RetrievalTAGWord Embeddings

PPEDCRF: Privacy-Preserving Enhanced Dynamic CRF for Location-Privacy Protection for Sequence Videos with Minimal Detection Degradation

2026-03-02 · Bo Ma, Jinsong Wu, Weiqi Yan, Catherine Shi 외 arxiv

Dashcam videos collected by autonomous or assisted-driving systems are increasingly shared for safety auditing and model improvement. Even when explicit GPS metadata are removed, an attacker can still infer the recording…

Object Detection

Tagging-Augmented Generation: Assisting Language Models in Finding Intricate Knowledge In Long Contexts

2025-10-27 · Anwesan Pal, Karen Hovsepian, Tinghao Guo, Mengnan Zhao 외 arxiv

Recent investigations into effective context lengths of modern flagship large language models (LLMs) have revealed major limitations in effective question answering (QA) and reasoning over long and complex contexts for e…

Question AnsweringData Augmentation