Search Results for author:
Found 6 papers, 2 papers with code
Image Search with Text Feedback by Additive Attention Compositional Learning
Effective image retrieval with text feedback stands to impact a range of real-world applications, such as e-commerce.
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.
Image Captioning: Transforming Objects into Words
Image captioning models typically follow an encoder-decoder architecture which uses abstract image feature vectors as input to the encoder.
Tag Prediction at Flickr: a View from the Darkroom
Our results demonstrate that, for real-world datasets, training exclusively with this noisy data yields performance on par with the standard paradigm of first pre-training on clean data and then fine-tuning.
A Large Contextual Dataset for Classification, Detection and Counting of Cars with Deep Learning
It would be easy to train this method to count other kinds of objects and counting over new scenes requires no extra set up or assumptions about object locations.
Ranked #9 on
Object Counting
on CARPK
Large-Scale Deep Learning on the YFCC100M Dataset
We train our three-layer deep neural network on the Yahoo!
