Search Results for author:
Found 2 papers, 0 papers with code
Similarity Comparisons for Interactive Fine-Grained Categorization
Current human-in-the-loop fine-grained visual categorization systems depend on a predefined vocabulary of attributes and parts, usually determined by experts.
Attribute-Based Detection of Unfamiliar Classes with Humans in the Loop
Recent work in computer vision has addressed zero-shot learning or unseen class detection, which involves categorizing objects without observing any training examples.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
