923 citations · 1.2k across the 5 of their papers we have counts for
6 papers
KEMP: Keyframe-Based Hierarchical End-to-End Deep Model for Long-Term Trajectory Prediction
Qiujing Lu, Weiqiao Han, Jeffrey Ling +4
Predicting future trajectories of road agents is a critical task for autonomous driving. Recent goal-based trajectory prediction methods, such as DenseTNT and PECNet, have shown go…
MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction
Balakrishnan Varadarajan, Ahmed Hefny, Avikalp Srivastava +8
Predicting the future behavior of road users is one of the most challenging and important problems in autonomous driving. Applying deep learning to this problem requires fusing het…
Identifying Driver Interactions via Conditional Behavior Prediction
Ekaterina Tolstaya, Reza Mahjourian, Carlton Downey +3
Interactive driving scenarios, such as lane changes, merges and unprotected turns, are some of the most challenging situations for autonomous driving. Planning in interactive scena…
TNT: Target-driveN Trajectory Prediction
Hang Zhao, Jiyang Gao, Tian Lan +9
Predicting the future behavior of moving agents is essential for real world applications. It is challenging as the intent of the agent and the corresponding behavior is unknown and…
YouTube-8M: A Large-Scale Video Classification Benchmark
Sami Abu-El-Haija, Nisarg Kothari, Joonseok Lee +4
Many recent advancements in Computer Vision are attributed to large datasets. Open-source software packages for Machine Learning and inexpensive commodity hardware have reduced the…
Efficient Large Scale Video Classification
Balakrishnan Varadarajan, George Toderici, Sudheendra Vijayanarasimhan +1
Video classification has advanced tremendously over the recent years. A large part of the improvements in video classification had to do with the work done by the image classificat…