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Found 4 papers, 2 papers with code
Training and challenging models for text-guided fashion image retrieval
Retrieving relevant images from a catalog based on a query image together with a modifying caption is a challenging multimodal task that can particularly benefit domains like apparel shopping, where fine details and subtle variations may be best expressed through natural language.
Modality-Agnostic Attention Fusion for visual search with text feedback
Image retrieval with natural language feedback offers the promise of catalog search based on fine-grained visual features that go beyond objects and binary attributes, facilitating real-world applications such as e-commerce.
Learning Embeddings for Product Visual Search with Triplet Loss and Online Sampling
Our approach significantly outperforms the state-of-the-art on the DeepFashion dataset.
Deep Architectures for Face Attributes
We train a deep convolutional neural network to perform identity classification using a new dataset of public figures annotated with age, gender, ethnicity and emotion labels, and then fine-tune it for attribute classification.
