activity
20162020
most citedMultimodal Model-Agnostic Meta-Learning via Task-Aware Modulation

72 citations · 94 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20205 cited

Visual Storytelling via Predicting Anchor Word Embeddings in the Stories

Bowen Zhang, Hexiang Hu, Fei Sha

We propose a learning model for the task of visual storytelling. The main idea is to predict anchor word embeddings from the images and use the embeddings and the image features jo…

cs.LG201972 cited

Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation

Risto Vuorio, Shao-Hua Sun, Hexiang Hu +1

Model-agnostic meta-learners aim to acquire meta-learned parameters from similar tasks to adapt to novel tasks from the same distribution with few gradient updates. With the flexib…

cs.CV20192 cited

Evaluating Text-to-Image Matching using Binary Image Selection (BISON)

Hexiang Hu, Ishan Misra, Laurens van der Maaten

Providing systems the ability to relate linguistic and visual content is one of the hallmarks of computer vision. Tasks such as text-based image retrieval and image captioning were…

cs.LG201813 cited

Toward Multimodal Model-Agnostic Meta-Learning

Risto Vuorio, Shao-Hua Sun, Hexiang Hu +1

Gradient-based meta-learners such as MAML are able to learn a meta-prior from similar tasks to adapt to novel tasks from the same distribution with few gradient updates. One import…

cs.CV20162 cited

Recalling Holistic Information for Semantic Segmentation

Hexiang Hu, Zhiwei Deng, Guang-tong Zhou +2

Semantic segmentation requires a detailed labeling of image pixels by object category. Information derived from local image patches is necessary to describe the detailed shape of i…