Papers › General Image Descriptors for Open World Image Retrieval using ViT CLIP

General Image Descriptors for Open World Image Retrieval using ViT CLIP

20 Oct 2022arXiv:2210.11141archive 2025-07-28

Marcos V. Conde, Ivan Aerlic, Simon Jégou

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 fundamental computer vision problem with notable applications in image retrieval, search engines and e-commerce. In this work, we explain our 4th place solution to the GUIE Challenge, and our "bag of tricks" to fine-tune zero-shot Vision Transformers (ViT) pre-trained using CLIP.

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Tasks

Image RetrievalRetrievalZero-Shot Image ClassificationZero-Shot LearningZero-shot Image Retrieval

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Methods

AdamAttentionAttention DropoutBPECLIPCosine AnnealingDense ConnectionsDiscriminative Fine-TuningDropoutGPTLayer NormalizationLinear LayerLinear Warmup With Cosine AnnealingMulti-Head AttentionResidual ConnectionSoftmaxWeight Decay

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