2nd Place Solution to Google Universal Image Embedding
Image representations are a critical building block of computer vision applications. This paper presents the 2nd place solution to the Google Universal Image Embedding Competition, which is part of the ECCV2022 instance-level recognition workshops. We use the instance-level fine-grained image classification method to complete this competition. We focus on data building and processing, model structure, and training strategies. Finally, the solution scored 0.713 on the public leaderboard and 0.709 on the private leaderboard.
Code (1)
Tasks
Fine-Grained Image Classificationimage-classificationImage ClassificationSimilar Papers 제목 키워드 기반
1st Place Solution in Google Universal Images Embedding
This paper presents the 1st place solution for the Google Universal Images Embedding Competition on Kaggle. The highlighted part of our solution is based on 1) A novel way to conduct training and fine-tuning; 2) The idea…
3rd Place Solution for Google Universal Image Embedding
This paper presents the 3rd place solution to the Google Universal Image Embedding Competition on Kaggle. We use ViT-H/14 from OpenCLIP for the backbone of ArcFace, and trained in 2 stage. 1st stage is done with freezed …
5th Place Solution to Kaggle Google Universal Image Embedding Competition
In this paper, we present our solution, which placed 5th in the kaggle Google Universal Image Embedding Competition in 2022. We use the ViT-H visual encoder of CLIP from the openclip repository as a backbone and train a …
6th Place Solution to Google Universal Image Embedding
This paper presents the 6th place solution to the Google Universal Image Embedding competition on Kaggle. Our approach is based on the CLIP architecture, a powerful pre-trained model used to learn visual representation f…
Transfer LearningGeneral Image Descriptors for Open World Image Retrieval using ViT CLIP
The Google Universal Image Embedding (GUIE) Challenge is one of the first competitions in multi-domain image representations in the wild, covering a wide distribution of objects: landmarks, artwork, food, etc. This is a …
Image RetrievalRetrievalZero-Shot Image ClassificationZero-shot Image Retrieval+1