Search Results for author:
Found 8 papers, 2 papers with code
Detecting and Matching Related Objects with One Proposal Multiple Predictions
Tracking players in sports videos is commonly done in a tracking-by-detection framework, first detecting players in each frame, and then performing association over time.
Learning Agent Representations for Ice Hockey
This paper develops a new approach for agent representations, based on a Markov game model, that is tailored towards applications in professional ice hockey.
Player Identification in Hockey Broadcast Videos
We propose an end-to-end trainable ResNet+LSTM network, with a residual network (ResNet) base and a long short-term memory (LSTM) layer, to discover spatio-temporal features of jersey numbers over time and learn long-term dependencies.
A Flow-Guided Mutual Attention Network for Video-Based Person Re-Identification
Our Mutual Attention network relies on the joint spatial attention between image and optical flow features maps to activate a common set of salient features across them.
Optical Flow Estimation
Video-Based Person Re-Identification
Group Activity Detection from Trajectory and Video Data in Soccer
Group activity detection in soccer can be done by using either video data or player and ball trajectory data.
Actor-Transformers for Group Activity Recognition
This paper strives to recognize individual actions and group activities from videos.
Optimizing Through Learned Errors for Accurate Sports Field Registration
We propose an optimization-based framework to register sports field templates onto broadcast videos.
Exploiting Prunability for Person Re-Identification
Then, these techniques are analysed according to their pruningcriteria and strategy, and according to different scenarios for exploiting pruningmethods to fine-tuning networks to target domains.
