most citedSpatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction

35 citations · 63 across the 4 of their papers we have counts for

collaborators

8 papers

cs.CV20205 cited

Towards Overcoming False Positives in Visual Relationship Detection

Daisheng Jin, Xiao Ma, Chongzhi Zhang +8

In this paper, we investigate the cause of the high false positive rate in Visual Relationship Detection (VRD). We observe that during training, the relationship proposal distribut…

cs.LG2020

Contrastive Variational Reinforcement Learning for Complex Observations

Xiao Ma, Siwei Chen, David Hsu +1

Deep reinforcement learning (DRL) has achieved significant success in various robot tasks: manipulation, navigation, etc. However, complex visual observations in natural environmen…

cs.LG2020

DinerDash Gym: A Benchmark for Policy Learning in High-Dimensional Action Space

Siwei Chen, Xiao Ma, David Hsu

It has been arduous to assess the progress of a policy learning algorithm in the domain of hierarchical task with high dimensional action space due to the lack of a commonly accept…

cs.LG2020

Balanced Meta-Softmax for Long-Tailed Visual Recognition

Jiawei Ren, Cunjun Yu, Shunan Sheng +4

Deep classifiers have achieved great success in visual recognition. However, real-world data is long-tailed by nature, leading to the mismatch between training and testing distribu…

cs.CV202035 cited

Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction

Cunjun Yu, Xiao Ma, Jiawei Ren +2

Understanding crowd motion dynamics is critical to real-world applications, e.g., surveillance systems and autonomous driving. This is challenging because it requires effectively m…

cs.LG202023 cited

Discriminative Particle Filter Reinforcement Learning for Complex Partial Observations

Xiao Ma, Peter Karkus, David Hsu +2

Deep reinforcement learning is successful in decision making for sophisticated games, such as Atari, Go, etc. However, real-world decision making often requires reasoning with part…