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02/03/2023
Reinforcement Learning and Distributed Model Predictive Control for Conflict Resolution in Highly Constrained Spaces
This work presents a distributed algorithm for resolving cooperative mul...
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11/02/2022
Multi-vehicle Conflict Resolution in Highly Constrained Spaces by Merging Optimal Control and Reinforcement Learning
We present a novel method to address the problem of multi-vehicle confli...
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04/17/2022
ParkPredict+: Multimodal Intent and Motion Prediction for Vehicles in Parking Lots with CNN and Transformer
The problem of multimodal intent and trajectory prediction for human-dri...
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11/19/2021
Meta Clustering Learning for Large-scale Unsupervised Person Re-identification
Unsupervised Person Re-identification (U-ReID) with pseudo labeling rece...
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07/01/2021
Revisiting Knowledge Distillation: An Inheritance and Exploration Framework
Knowledge Distillation (KD) is a popular technique to transfer knowledge...
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03/29/2021
Cloth-Changing Person Re-identification from A Single Image with Gait Prediction and Regularization
Cloth-Changing person re-identification (CC-ReID) aims at matching the s...
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03/16/2021
Dense Interaction Learning for Video-based Person Re-identification
Video-based person re-identification (re-ID) aims at matching the same p...
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11/26/2020
Spatio-Temporal Inception Graph Convolutional Networks for Skeleton-Based Action Recognition
Skeleton-based human action recognition has attracted much attention wit...
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11/01/2020
Collision Avoidance in Tightly-Constrained Environments without Coordination: a Hierarchical Control Approach
We present a hierarchical control approach for maneuvering an autonomous...
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04/21/2020
ParkPredict: Motion and Intent Prediction of Vehicles in Parking Lots
We investigate the problem of predicting driver behavior in parking lots...
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11/28/2019
Transform-Invariant Convolutional Neural Networks for Image Classification and Search
Convolutional neural networks (CNNs) have achieved state-of-the-art resu...
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11/28/2019
Patch Reordering: a Novel Way to Achieve Rotation and Translation Invariance in Convolutional Neural Networks
Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art ...
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11/28/2019
Continuous Dropout
Dropout has been proven to be an effective algorithm for training robust...
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11/21/2019
