Efficient large-scale image retrieval with deep feature orthogonality and Hybrid-Swin-Transformers

7 October 2021

Papers citing "Efficient large-scale image retrieval with deep feature orthogonality and Hybrid-Swin-Transformers"

5 / 5 papers shown

Title
Bent & Broken Bicycles: Leveraging synthetic data for damaged object re-identification Luca Piano F. G. Pratticó Alessandro Sebastian Russo Lorenzo Lanari Lia Morra Fabrizio Lamberti 11 1 0 16 Apr 2023
2nd Place Solution to Google Universal Image Embedding Xiaolong Huang Qiankun Li SSL 11 2 0 17 Oct 2022
Google Landmark Retrieval 2021 Competition Third Place Solution Qishen Ha Bo Liu Hongwei Zhang 3DV 3DPC 13 2 0 09 Oct 2021
DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features Min Yang Dongliang He M. Fan Baorong Shi Xuetong Xue Fu Li Errui Ding Jizhou Huang 35 92 0 06 Aug 2021
WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning Krishna Srinivasan K. Raman Jiecao Chen Michael Bendersky Marc Najork VLM 197 308 0 02 Mar 2021