Search Results for author:
Found 5 papers, 2 papers with code
Semi-Supervised Semantic Image Segmentation with Self-correcting Networks
Building a large image dataset with high-quality object masks for semantic segmentation is costly and time consuming.
Hierarchical Relational Networks for Group Activity Recognition and Retrieval
Second, we propose a Relational Autoencoder model for unsupervised learning of features for action and scene retrieval.
Active Learning for Structured Prediction from Partially Labeled Data
We propose a general purpose active learning algorithm for structured prediction, gathering labeled data for training a model that outputs a set of related labels for an image or video.
Generic Tubelet Proposals for Action Localization
Our class-independent TPN outperforms other tubelet generation methods, and our unified temporal deep network achieves state-of-the-art localization results on all three datasets.
Hierarchical Deep Temporal Models for Group Activity Recognition
In order to model both person-level and group-level dynamics, we present a 2-stage deep temporal model for the group activity recognition problem.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
